Technocracy

From Wikipedia, the free encyclopedia

https://en.wikipedia.org/wiki/Technocracy

Technocracy is a form of government in which the decision-makers are selected based on their expertise in a given area of responsibility, particularly with regard to scientific or technical knowledge. Technocracy follows largely in the tradition of other meritocratic theories and assumes full state control over political and economic issues.

This system explicitly contrasts with representative democracy, the notion that elected representatives should be the primary decision-makers in government, though it does not necessarily imply eliminating elected representatives. Decision-makers are selected based on specialized knowledge and performance rather than political affiliations, parliamentary skills, or popularity.

The term technocracy was initially used to signify the application of the scientific method to solving social problems. In its most extreme form, technocracy is an entire government running as a technical or engineering problem and is mostly hypothetical. In more practical use, technocracy is any portion of a bureaucracy run by technologists. A government in which elected officials appoint experts and professionals to administer individual government functions, and recommend legislation, can be considered technocratic. Some uses of the word refer to a form of meritocracy, where the ablest are in charge, ostensibly without the influence of special interest groups. Critics have suggested that a "technocratic divide" challenges more participatory models of democracy, describing these divides as "efficacy gaps that persist between governing bodies employing technocratic principles and members of the general public aiming to contribute to government decision making".

History of the term

The term technocracy is derived from the Greek words τέχνη, tekhne meaning skill and κράτος, kratos meaning power, as in governance, or rule. William Henry Smyth, a California engineer, is usually credited with inventing the word technocracy in 1919 to describe "the rule of the people made effective through the agency of their servants, the scientists and engineers", although the word had been used before on several occasions. Smyth used the term Technocracy in his 1919 article "'Technocracy'—Ways and Means to Gain Industrial Democracy" in the journal Industrial Management (57). Smyth's usage referred to Industrial democracy: a movement to integrate workers into decision-making through existing firms or revolution.

In the 1930s, through the influence of Howard Scott and the technocracy movement he founded, the term technocracy came to mean 'government by technical decision making', using an energy metric of value. Scott proposed that money be replaced by energy certificates denominated in units such as ergs or joules, equivalent in total amount to an appropriate national net energy budget, and then distributed equally among the North American population, according to resource availability.

There is in common usage found the derivative term technocrat. The word technocrat can refer to someone exercising governmental authority because of their knowledge, "a member of a powerful technical elite", or "someone who advocates the supremacy of technical experts". McDonnell and Valbruzzi define a prime minister or minister as a technocrat if "at the time of their appointment to government, they: have never held public office under the banner of a political party; are not a formal member of any party; and are said to possess recognized non-party political expertise which is directly relevant to the role occupied in government". In Russia, the President of Russia has often nominated ministers based on technical expertise from outside political circles, and these have been referred to as "technocrats".

Precursors

Before the term technocracy was coined, technocratic or quasi-technocratic ideas involving governance by technical experts were promoted by various individuals, most notably early socialist theorists such as Henri de Saint-Simon. This was expressed by the belief in state ownership over the economy, with the state's function being transformed from pure philosophical rule over men into a scientific administration of things and a direction of production processes under scientific management. According to Daniel Bell:

"St. Simon's vision of industrial society, a vision of pure technocracy, was a system of planning and rational order in which society would specify its needs and organize the factors of production to achieve them."

Citing the ideas of St. Simon, Bell concludes that the "administration of things" by rational judgment is the hallmark of technocracy.

Alexander Bogdanov, a Russian scientist and social theorist, also anticipated a conception of technocratic process. Both Bogdanov's fiction and his political writings, which were highly influential, suggest that he was concerned that a coming revolution against capitalism could lead to a technocratic society.

From 1913 until 1922, Bogdanov immersed himself in writing a lengthy philosophical treatise of original ideas, Tectology: Universal Organization Science. Tectology anticipated many basic ideas of systems analysis, later explored by cybernetics. In Tectology, Bogdanov proposed unifying all social, biological, and physical sciences by considering them as systems of relationships and seeking organizational principles that underlie all systems.

Arguably, the Platonic idea of philosopher-kings represents a sort of technocracy in which the state is run by those with specialist knowledge, in this case, knowledge of the Good rather than scientific knowledge. The Platonic claim is that those who best understand goodness should be empowered to lead the state, as they would lead it toward the path of happiness. Whilst knowledge of the Good differs from knowledge of science, rulers are here appointed based on a certain grasp of technical skill rather than democratic mandate.

Characteristics

Technocrats are individuals with technical training and occupations who perceive many important societal problems as being solvable with the applied use of technology and related applications. The administrative scientist Gunnar K. A. Njalsson theorizes that technocrats are primarily driven by their cognitive "problem-solution mindsets" and only in part by particular occupational group interests. Their activities and the increasing success of their ideas are thought to be a crucial factor behind the modern spread of technology and the largely ideological concept of the "information society". Technocrats may be distinguished from "econocrats" and "bureaucrats" whose problem-solution mindsets differ from those of the technocrats.

Examples

The former government of the Soviet Union has been referred to as a technocracy. Soviet leaders like Leonid Brezhnev often had a technical background. In 1986, 89% of Politburo members were engineers.

Leaders of the Chinese Communist Party used to be mostly professional engineers. According to surveys of municipal governments of cities with a population of 1 million or more in China, it has been found that over 80% of government personnel had a technical education. Under the five-year plans of the People's Republic of China, projects such as the National Trunk Highway System, the China high-speed rail system, and the Three Gorges Dam have been completed. During China's 20th National Congress, a class of technocrats in finance and economics are replaced in favor of high-tech technocrats.

In 2013, a European Union library briefing on its legislative structure referred to the Commission as a "technocratic authority", holding a "legislative monopoly" over the EU lawmaking process. The briefing suggests that this system, which elevates the European Parliament to a vetoing and amending body, was "originally rooted in the mistrust of the political process in post-war Europe". This system is unusual since the Commission's sole right of legislative initiative is a power usually associated with Parliaments.

Several governments in European parliamentary democracies have been labelled 'technocratic' based on the participation of unelected experts ('technocrats') in prominent positions. Since the 1990s, Italy has had several such governments (in Italian, governo tecnico) in times of economic or political crisis, including the formation in which economist Mario Monti presided over a cabinet of unelected professionals. The term 'technocratic' has been applied to governments where a cabinet of elected professional politicians is led by an unelected prime minister, such as in the cases of the 2011-2012 Greek government led by economist Lucas Papademos and the Czech Republic's 2009–2010 caretaker government presided over by the state's chief statistician, Jan Fischer. In December 2013, in the framework of the national dialogue facilitated by the Tunisian National Dialogue Quartet, political parties in Tunisia agreed to install a technocratic government led by Mehdi Jomaa.

The article "Technocrats: Minds Like Machines" states that Singapore is perhaps the best advertisement for technocracy: the political and expert components of the governing system there seem to have merged completely. This was underlined in a 1993 article in "Wired" by Sandy Sandfort, where he describes the information technology system of the island even at that early date making it effectively intelligent.

Engineering

Following Samuel Haber, Donald Stabile argues that engineers were faced with a conflict between physical efficiency and cost efficiency in the new corporate capitalist enterprises of the late nineteenth-century United States. Because of their perceptions of market demand, the profit-conscious, non-technical managers of firms where the engineers work often impose limits on the projects that engineers desire to undertake.

The prices of all inputs vary with market forces, thereby upsetting the engineer's careful calculations. As a result, the engineer loses control over projects and must continually revise plans. To maintain control over projects, the engineer must attempt to control these outside variables and transform them into constant factors.

Technocracy movement

Main article: Technocracy movement

The American economist and sociologist Thorstein Veblen was an early advocate of technocracy and was involved in the Technical Alliance, as were Howard Scott and M. King Hubbert (the latter of whom later developed the theory of peak oil). Veblen believed technological developments would eventually lead to a socialistic reorganization of economic affairs. Veblen saw socialism as one intermediate phase in an ongoing evolutionary process in society that would be brought about by the natural decay of the business enterprise system and the rise of the engineers. Daniel Bell sees an affinity between Veblen and the Technocracy movement.

In 1932, Howard Scott and Marion King Hubbert founded Technocracy Incorporated and proposed that money be replaced by energy certificates. The group argued that apolitical, rational engineers should be vested with the authority to guide an economy into a thermodynamically balanced load of production and consumption, thereby doing away with unemployment and debt.

The technocracy movement was briefly popular in the US in the early 1930s during the Great Depression. By the mid-1930s, interest in the movement was declining. Some historians have attributed the decline to the rise of Roosevelt's New Deal.

Historian William E. Akin rejects this conclusion. Instead, Akin argues that the movement declined in the mid-1930s due to the technocrats' failure to devise a 'viable political theory for achieving change'. Akin postulates that many technocrats remained vocal, dissatisfied, and often sympathetic to anti-New Deal third-party efforts.

Critiques

Critics have suggested that a "technocratic divide" exists between a governing body controlled to varying extents by technocrats and members of the general public. Technocratic divides are "efficacy gaps that persist between governing bodies employing technocratic principles and members of the general public aiming to contribute to government decision making." Technocracy privileges the opinions and viewpoints of technical experts, exalting them into a kind of aristocracy while marginalizing the opinions and viewpoints of the general public.

As major multinational technology corporations (e.g., FAANG) swell market caps and customer counts, critiques of technocratic government in the 21st century see its manifestation in American politics not as an "authoritarian nightmare of oppression and violence" but rather as an éminence grise: a democratic cabal directed by Mark Zuckerberg and the entire cohort of "Big Tech" executives. In his 1982 Technology and Culture journal article, "The Technocratic Image and the Theory of Technocracy", John G. Gunnell writes: "...politics is increasingly subject to the influence of technological change", with specific reference to the advent of The Long Boom and the genesis of the Internet, following the 1973–1975 recession. Gunnel goes on to add three levels of analysis that delineate technology's political influence:

1. "Political power tends to gravitate towards technological elites".
2. "Technology has become autonomous" and thus impenetrable by political structures.
3. "Technology (and science) constitute a new legitimizing ideology", as well as triumphing over "tribalism, nationalism, the crusading spirit in religion, bigotry, censorship, racism, persecution, immigration and emigration restrictions, tariffs, and chauvinism".

In each of the three analytical levels, Gunnell foretells technology's infiltration of political processes and suggests that the entanglement of the two (i.e. technology and politics) will inevitably produce power concentrations around those with advanced technological training, namely the technocrats. Forty years after the publication of Gunnell's writings, technology and government have become, for better or for worse, increasingly intertwined. Facebook can be considered a technocratic microcosm, a "technocratic nation-state" with a cyberspatial population that surpasses any terrestrial nation. In a broader sense, critics fear that the rise of social media networks (e.g. Twitter, YouTube, Instagram, Pinterest), coupled with the "decline in mainstream engagement", imperil the "networked young citizen" to inconspicuous coercion and indoctrination by algorithmic mechanisms, and, less insidiously, to the persuasion of particular candidates based predominantly on "Social Media engagement".

In a 2022 article published in Boston Review, political scientist Matthew Cole highlights two problems with technocracy: that it creates "unjust concentrations of power" and relies on a "flawed theory of knowledge". With respect to the first point, Cole argues that technocracy excludes citizens from policy-making processes while advantaging elites. With respect to the second, he argues that the value of expertise is overestimated in technocratic systems, and points to an alternative concept of "smart democracy" which enlists the knowledge of ordinary citizens.

Digital health

From Wikipedia, the free encyclopedia

https://en.wikipedia.org/wiki/Digital_health

Digital health is a discipline that includes digital care programs, technologies with health, healthcare, living, and society to enhance the efficiency of healthcare delivery and to make medicine more personalized and precise. It uses information and communication technologies to facilitate understanding of health problems and challenges faced by people receiving medical treatment and social prescribing in more personalised and precise ways. The definitions of digital health and its remits overlap in many ways with those of health and medical informatics.

Worldwide adoption of electronic medical records has been on the rise since 1990. Digital health is a multi-disciplinary domain involving many stakeholders, including clinicians, researchers and scientists with a wide range of expertise in healthcare, engineering, social sciences, public health, health economics and data management.

Digital health technologies include both hardware and software solutions and services, including telemedicine, wearable devices, augmented reality, and virtual reality. Generally, digital health interconnects health systems to improve the use of computational technologies, smart devices, computational analysis techniques, and communication media to aid healthcare professionals and their patients manage illnesses and health risks, as well as promote health and wellbeing.

Although digital health platforms enable rapid and inexpensive communications, critics warn against potential privacy violations of personal health data and the role digital health could play in increasing the health and digital divide between social majority and minority groups, possibly leading to mistrust and hesitancy to use digital health systems.

Elements

The prominence of Digital health in the past century has culminated for the emergence of three reasons, stated by both Professor John Powell and Professor Theodoros N Arvanitis "the development of new technologies... and also trends towards smart, wearable and pervasive technologies; the need for health services to find new approaches to addressing the demands of an ageing population... and the role of the empowered patient and the shift in models of health service delivery towards patient-centred care, and patient-led care." These three points have directed and motivated the rise in the elements that play a crucial role in the creation of Digital health care services.

Primary Care Services

The first group of these services is known as primary care services in the domain of digital health. These services include wireless medical devices that utilize technology such as Wi-Fi or Bluetooth, as well as applications on mobile devices that encourage the betterment of an individual's health as well as applications that promote overall general wellness. For example, researchers developed a digital service to help elderly people with balance disorder and risk of falling. As prominent sociologist Deborah Lupton states, "Health promoters have experimented with using text messages, social media sites and apps to disseminate information about preventive health, collect data about people's health-related behaviours and attempt to 'nudge' members of target groups to change their behaviour in the interests of their health." In other words, Lupton states that various media technologies that can be found on mobile devices are being utilized to try and better certain groups' behaviors in concern with digital health.

Acute Care Services

The second group of these services is known as acute care in the digital health domain. These services include telemedicine which is defined as handling patients over some sort of streaming device and is targeted towards areas where the population is more widely scattered, medical devices that incorporate different aspects of software otherwise known as SaMD, and examples of these devices are pacemakers. The final example of acute care services is the 'interoperability' of 'Health IT, Cybersecurity, and Medical Devices', Health IT is how the electronic database stores, processes, and analyses personal health information and how this information can be utilized by medical personnel and organizations around the world of easier access of information, Cybersecurity which then plays into the storing of personal health information in how this information is secured and protected in the interest of personal safety of the individuals whose information is being stored, and Medical Devices that are able to communicate within each other to better care for a patient by transmitting what needs to be done on one machine to another. Sociologist Deborah Lupton states "However, members of some social groups are currently excluded from full participation in the digital health ecosystem. Mechanisms for facilitating further consultation between the various stakeholders involved in digital health, including patients and carers, need to be established. The rights and responsibilities of the different stakeholders involved in connected digital health also need to be better identified and highlighted. At the same time, personal data privacy and security need protection." Lupton concludes that despite the innovation of various elements in this digital health area, there are still multiple issues that need to be organized and dealt with for the continuation of the revolution of Digital Health.

Other Digital Health Elements

The rest of the elements of Digital health that do not fall so squarely into acute or primary care services are listed as the transmission of medical education and information between practitioners and researchers through the utilization of digital technologies and applications that can be employed by doctors for risk-assessment regarding patients. Devices that can be utilized for the improvement and management of bodily purposes as well as the encouragement of the education of digital health to the public. There are also patient-based applications that can be utilized to share information by individual patients as well as encourage the usage of drug trials. The tracking of outbreaks of disease by the use of mass media that social media has developed has also come about through Digital Health. Finally the recording of the environment around sensor devices that are being utilized for the betterment of the community.

Technologies

Digital health technologies come in many different forms and extend into various parts of healthcare. As new technologies develop, digital health, as a field, respectively transforms. The three most popular domains of digital health technologies include telemedicine, wearable technologies, and augmented and virtual reality. Telemedicine is how physicians treat patients remotely and the different technologies needed to make the process more efficient and faster. The other main side of digital health is data collection and how to provide on-demand medical information for patients, which gave rise to wearables. Wearable technologies hold the promise of bringing personalized data and health-related tracking to all users. In terms of digitized treatment, augmented and virtual reality can create personalized regimens for patients that can be repeated and tailored to treat many conditions.

In fact some of these technologies are being propelled by the startup space, which has been followed via Internet or online media sources such as podcasts on digital health entrepreneurs. The National Institute for Health and Care Research (NIHR) has published a review of research on how digital health technologies can help manage health conditions.

Electronic medical records (EMRs)

One of the most used E-health applications worldwide is electronic medical records (EMRs). Electronic medical records have multiple functions in the medical field. Some of the functions include but are not limited to documentation, communication, and management of patient data. Electronic medical records are the technological replacement for paper-based documentation, which is not only labor-intensive but also repetitive, inaccurate at times, and can consume a lot of time. Electronic Health Records (EHRs) are another E-health application used by physicians. However, despite the many similarities in both health applications, they are not the same. The main difference between the two is that EHRs have an additional feature which includes the ability to share the data for multiple authorized physicians.

Telemedicine

Telemedicine, also known as telehealth, is a way for patients to interact with their doctors virtually. According to the National Library of Medicine (NIH), the definition of telehealth is "the use of electronic information and communications technologies to provide and support health care when distance separates the participants." Telehealth is an umbrella term that encompasses various applications of electronics in medicine. The more common uses of technology involve calling patients to let them know their lab results are in or communication between emergency departments. On the other hand, there are more complex uses of technology called telesurgery. While there are two extremes of the uses of telehealth, the more recent applications of telehealth involve patient and healthcare-professional interaction.

Applications

There is a wide range of applications of telemedicine while having patient and doctor interaction. One example is disorders that do not require lab tests and investigations. One of the medical fields pertaining to this example is mental health. The only tools a patient needs are a phone, laptop, or device with video conferencing capabilities, allowing them to connect with their therapist to receive live consultations. Another application is virtual doctor's appointments. After the worldwide impact of COVID-19, patients’ willingness to enter a doctor’s office where there are germs and people with different health issues for a regular checkup is low. Through the use of video conferencing, telemedicine allows patients to have their yearly checkups from the comfort of their homes. This eliminates long wait times and commuting and provides a familiar environment for the patient to open up to the healthcare provider. Another application of telehealth involving patient care is dermatology. The patient can hold high-resolution devices to their skin and allow the dermatologist to gauge what needs to be addressed. Additionally, this method is ideal to conduct check-in visits that ensure rashes or skin conditions are healing properly.

Benefits

The benefits of telehealth are vast and stem from its application. One of the benefits of telehealth is the time-saving element. Patients no longer have to think of wait times in hospitals and offices or spend commuting to and from doctors’ appointments. Instead, they can log onto their device and see their healthcare professional virtually. This is especially beneficial for those who live in rural areas where specialized hospitals are scarce and far away. The public now has access to doctors who specialize in certain diseases instead of having to drive and commute long distances to have a simple consultation meeting. Additionally, patients no longer have to worry about taking an entire day off work for a regular health checkup. They can simply block out enough time that is required for their appointment which results in fewer travel costs, less need to find childcare services, and privacy. Another benefit of telehealth is the reduction in face-to-face contact. By using video conferencing, patients are less likely to contract germs from others at the hospital and limit the spread of germs themselves.

Limitations

Although vast in its benefits, due to the rapid expansion of telehealth during COVID-19, various limitations arise while using telemedicine. A common criticism of telehealth is that it can feel impersonal, as doctors and patients do not meet face-to-face. This lack of in-person communication can result in improper patient histories and physical examinations. It is important to remember that online visits should only occur when in-person care is not needed. Another obstacle to using telehealth is the potential for technical difficulties and concerns about security breaches. Moreover, the rules and regulations governing telemedicine vary by state and are always changing. According to The Journal for Nurse Practitioners, “The rapid expansion of telehealth, especially during the COVID-19 pandemic, paired with variable regulations and guidelines creates increased potential for liability and legal issues.” 

Digital healthcare interventions

Digital healthcare interventions (DHI) has been used to a wide range of applications across various aspects of healthcare, such as self-management tools, where patients use applications and platforms to manage chronic conditions like diabetes or hypertension; self-education and health promotion tools, that provide educational material designed to leverage the population's knowledge regarding one specific health topic and promote healthy behaviors, and digital therapeutics (software-based interventions designed to prevent, manage, or treat medical disorders).

Wearable technology

Wearable technology comes in many forms, including smartwatches and on-body sensors. Smartwatches were one of the first wearable devices that promoted self-monitoring and were typically associated with fitness tracking. Many record health-related data, such as "body mass index, calories burnt, heart rate, physical activity patterns". Such technology is increasingly being available in conventional Smartphones including the iPhone IPhone, which contains a built in heart monitor. Beyond smartwatches, researchers are developing smart-related bodywear, like patches, clothes, and accessories, to administer "on-demand drug release". This technology can expand into smart implants for both severe and non-severe medical cases, where doctors will be able to create better, dynamic treatment protocols that would not have been possible without such mobile technology.

These technologies are used to gather data on patients at all times during the day. Since doctors no longer need to have their patients come into the office to collect the necessary data, being downloaded automatically, the data can lead to better treatment plans and patient monitoring. Doctors will have better knowledge into how well a certain medication is performing. They will also be able to continuously learn from this data and improve upon their original treatment plans to intervene when needed.

Augmented and virtual reality

In digital health, augmented reality technology enhances real-world experiences with computerized sensory information and is used to build smart devices for healthcare professionals. Since the majority of patient-related information now comes from hand-held devices, smart glasses provide a new, hands-free augmented way for a doctor to view their patient's medical history. The applications of this technology can extend into data-driven diagnosis, augmented patient documentation, or even enhanced treatment plans, all by wearing a pair of smart glasses when treating a patient, although planning is recommended to ensure equity, and that the highest ethical standards are upheld as planning moves forward and regulatory frameworks are developed.

Another similar technology space is virtual reality, which creates interactive simulations that mimic real-life scenarios and can be tailored for personalized treatments. Many stroke victims lose range of motion and under standard treatment protocols; 55% to 75% of patients have long-term upper muscular dysfunction, as the lower body is primarily targeted during therapy. Repeated actions and the length of therapy are the two main factors that show positive progress towards recovery. Virtual reality technologies can create various 3D environments that are difficult to replace in real-life but are necessary to help patients retrain their motor movements. These simulations can not only target specific body parts, but can also increase in intensity as the patient improves and requires more challenging tasks.

Robotics

A wide range of robotic technology has been used in medical contexts. A notable example being in robot assisted surgery. A good example is the Da Vinci Robotic Surgery System developed by Intuitive Surgery Da Vinci Surgical System. This semi-automatic robot, allows a surgeon to remotely perform surgery. The robot performing incisions as directed the surgeon observing via screen.

Others

Some other technologies include Assistive technologies, rehabilitation robotics, and unobtrusive monitoring sensors that can help people with disabilities perform their daily tasks independently. Computational simulations, modeling, and machine learning (e.g. FG-AI4H) approaches can model health-related outcomes. These advanced simulations are able to be repeated, replicated, and tailored to any research area. In medical imaging, the applications for this technology helps healthcare professionals visualize genes, brain structures, and many other components of human anatomy. The flexibility in this technology also allows for more positive and accurate results. Mobile health (or mhealth) is the practice of medicine and public health supported by mobile devices.

Health systems engineering is another subset of digital health that leverages other engineering industries to improve upon applications include knowledge discovery, decision making, optimization, human factors engineering, quality engineering, and information technology and communication. Speech and hearing systems for natural language processing, speech recognition techniques, and medical devices can aid in speech and hearing (e.g. cochlear implants). Digital hearing aids use various algorithms to reduce background noises and improve perceptual performance, which is a significant improvement from regular hearing implants.

Implementation

National electronic health record (EHR) systems National digital programs exist to support healthcare, form meaningful indicators, and facilitate population-based studies by providing clinically procured data in an open-source and standardized digital format. These can inform public health decisions, which are especially crucial in low-resource settings. The World Health Organization's Global Observatory for eHealth (GOe) conducts and reports a worldwide survey of its 194 member nations on their progress towards EHR implementation as well as universal healthcare coverage. In their latest issue in 2015, 73 Members (58%) responded with having some eHealth strategy in place, a count that has increased since 1990. Within this cohort, high-income countries are overrepresented, as well as the majority are countries with universal health care (UHC).

National digital programs exist to support healthcare, such as those of Canada Health Infoway built on core systems of patient and provider registries, clinical and diagnostic imaging systems, clinical reports and immunizations. By 2014, 75% of Canadian physicians were using electronic medical records.

In Uganda and Mozambique, partnerships between patients with cell phones, local and regional governments, technologists, non-governmental organizations, academia, and industry have enabled mHealth solutions.

In the United Kingdom, the National Health Service (NHS) has commissioned a report on how to integrate digital healthcare technologies into the next generation of medicine. The "Topol Review" recommended an expansion of education for both patients and providers of next-generation technologies such as Whole Genome Sequencing, and has also created Digital Fellowships for health professionals. The United States has also embarked on a nationwide health study known as 'All of Us" to bring together a variety of health indicators in a digital format for researchers around the world.

On the other hand, the implementation of these innovations has also brought to light societal risks and regulatory needs, which are certainly challenging the current governance structures in the health sector.

Innovation cycle

The innovation process for digital health is an iterative cycle for technological solutions that can be classified into five main activity processes from the identification of the healthcare problem, research, digital solution, and evaluating the solution, to implementation in working clinical practices. Digital health may incorporate methods and tools adopted by software engineering, such as design thinking and agile software development. These commonly follow a user-centered approach to design, which are evaluated by subject-matter experts in their daily life using real-world data.

U.S. Food and Drug Administration

In 2019, the FDA published a Digital Health Innovation Action Plan that planned to reduce inefficiencies for physicians in an effort to cut overhead costs, improve access, increase quality of service, and make medicine more easily adapted for each person. Topics within the innovation plan are wireless devices, telemedicine, software, and cybersecurity, among others. According to FDA guidelines, if you release an app designed to help someone with a medical condition then that is considered a medical device. The FDA cannot regulate all healthcare apps, so they use "enforcement discretion", and up until 2020, have chosen not to regulate all digital care programs and apps. However, programs that use the word treatment, seek to diagnose or treat a condition, or are deemed unsafe, are and will be regulated by the FDA. During the COVID-19 pandemic, regulations and enforcement of digital psychiatry apps were relaxed to facilitate use and reduce in-person contact.

International Standards

At an intergovernmental level, the World Health Organization is the United Nations Specialized Agency for health, and the International Telecommunication Union is the UN Specialized Agency for ICTs, the Agencies collaborate in their work on digital health, such as the H.870 standard on safe listening, as well as the ITU-WHO Focus Group on Artificial Intelligence for Health, a subsidiary of the ITU-T Study Group 16.

In traditional healthcare, doctors conducted medical practices with a limited number of tools, and got more experienced over time. Since becoming a doctor required experience and knowledge, very few took up the profession. The lack of communication between people in different places caused new technology to spread slowly. Since doctors were seen as experts in their fields, patients would have very little decision on how they were treated. Although there's been an extensive change in technology, the current health care system doesn't reflect on the changes in treatments. During the 2010s, healthcare knowledge continued to grow rapidly, and patients began to get frustrated due to the vast knowledge out there that physicians didn't know or use. The number of and the cost to treat chronic illnesses increased, and the World Health Organization estimated that there was a worldwide shortage of 4.3 million healthcare workers. During the transition from traditional healthcare to digital health, the amount of access to high quality health technology and medical records and studies increased. The transition also gave patients the option of self-care because not only did it change the technology accessible to patients, but also the patients' ability to choose their way of treatment. Although this new way of treatment has given patients a role in treatment, it has led to difficulty with patients choosing the best treatment options. According to the article, Digital Health is a Cultural Transformation of Traditional Healthcare from the National Library of Medicine, "The success of providing care depends on collaboration, empathy and shared decision making. What is needed for this is a newly defined co-operation between patients and their caregivers." In this quote, health care experts explain that they need to collaborate with patients and respect their decisions in choosing treatment options for them. The article then explains how a strong relationship between physicians and patients help influence what treatment options they choose, and how empathy is an important characteristic for physicians to have.

In May 2018, the World Health Organization passed a global strategy for digital health. There were four major goals for the strategy. The first goal was for nations and companies to collaborate more in making new treatments and technology. Two other main goals for the strategy were to increase the implementation of national strategies towards digital health, and to increase authority over digital health from global to national levels. The World Health Organization also made guidelines in regulating certifying digital health medical devices similar to how medicine and vaccines are tested. The strategy was also made to list health data as a public health good, and made an outline for how research and data are shared, and how Artificial Intelligence is used. It even endorsed people-centered health systems that used digital health. While the World Health Organization was pushing their strategy, other groups are also developing strategies to make digital health more available in communities that don't have it.

Before this strategy was published, the World Health Organization made a plan around the beginning of 2015 to use digital health to end Tuberculosis. The following reasons why this strategy was passed included how health care managers didn't have the resources for prevention of Tuberculosis. There was a need for a step to step plan to include digital health for the End TB Strategy. The plan would also give opportunity to improve health care technology and increase efficiency and sustainability of efforts. The plan focused on treating and preventing tuberculosis, and giving treatment options for patients suffering from Tuberculosis from national to international levels. the following steps included functional laboratory information included using digital technologies to diagnose patients, providing secure data transmission and storage, and using data to store patients' results. Some of the technologies used in the campaign were Video Treatment Support, and eHealth Portal.

Criticisms

Digital healthcare presents a wide range of complex and sometimes novel regulatory challenges, including questions about how to balance public interest concerns against an individual's right to privacy as well as the risks of 'pseudo-experts' providing medical advice. Meanwhile, the explosion in the number of uses and applications seen during the COVID-19 pandemic has also brought to light the limitations of existing legislation and other regulatory tools to grapple with these concerns (or, in some cases, been enabled by changes in legislation that groups such as the Varieties of Democracy have argued have produced a 'pandemic backslide' in human rights protections).

Ownership of health data

At a global level, the implementation of digital health solutions depends on large data sets, ranging from simple statistics that record every birth and death to more sophisticated metrics that track diseases, outbreaks, and chronic conditions. These systems record data such as patient records, blood test results, EKGs, MRIs, billing records, drug prescriptions, and other private medical information. Medical professionals can use this data to make more data-driven decisions about patient care and consumers themselves can utilize it to make informed choices about their own health. Given the personal nature of the data being collected, a crucial debate has arisen amongst stake-holders about one of the challenges induced by digital health solutions: the ownership of health data. In most cases, governments and big data and technology companies are storing citizens' medical information, leaving many concerned with how their data is being used and/or who has access to it. This is further compounded by the fact that the details that answer these questions is oftentimes hidden in complex terms & conditions that are rarely read. A notable example of a data privacy breach in the digital health space took place in 2016. Google faced a major lawsuit over a data-sharing agreement that gave its artificial intelligence arm, DeepMind, access to the personal health data of 1.6 million British patients. Google failed to secure patient consent and guarantee the anonymity of the patients. Another concept is that data is considered as a form of public good. Researchers from Stanford University proposed the use of such a framework, to think about data and the development of AI; they were thinking about radiology data specifically. They concluded that clinical data should be a form of public good, used for the benefit of future patients and that the data should be widely available for the development of knowledge and tools to benefit future patients. From this, they drew three main conclusions. Firstly, if the clinical data is really not owned by anyone, those who interact with it then have an obligation to ensure that the data is used for the benefit of future patients in societies. Secondly, this data should be widely shared for research and development, and all the individuals and entities with access to that data, then essentially become stewards of that data and become responsible to carefully safeguard the privacy and to ensure that the data is used for developing knowledge and tools for the good. Thirdly, patient consent would not necessarily be required before the data is used for secondary purposes, such as AI development and training and testing, as long as there are mechanisms in place to ensure that ethical standards are being followed. According to this proposed framework, the authors propose that it would be unethical to sell data to the third parties by granting exclusive access in exchange for monetary or any kind of payments that exceed costs.

Misinterpretation of data

Although the data and information provided by personalized health platforms may give reassurance to users, they might simultaneously induce increased anxiety and obsessive behavior. As seen with platforms like WebMD, the misinterpretation of data can further contribute to patient hysteria: having increased access to information on oneself is not always positive. In an extreme scenario, patients might feel a misplaced sense of security knowing that they have this access, meaning that they won't seek medical advice or help from professionals, even if it may be needed.

Institutional ageism

Ageism is defined as the process of systemic discrimination against the elderly. As digital health becomes more prevalent in our society, those who lack strong digital skills and the technical know-how needed to navigate these platforms will be put at a disadvantage. This doesn't just apply to current seniors. New digital technologies become popularized every year rendering older technology obsolete. This means that this digital divide will always be present, unless health companies actively work to try to minimize this gap. Not to mention, seniors are more prone to chronic health issues, meaning that they are one of the groups that has the greatest need for a digital health platform. They represent an untapped user group.

Challenges in implementing digital health technologies

Multiple studies have shown challenges in implementing digital health technologies in a variety of settings. There is a need to rethink digital health technologies to accommodate diverse user requirements with flexible, adaptable tools. A robust implementation strategy and effective training programs are crucial for addressing specific needs and managing information overload. The often-overlooked importance of clinician experiences suggests that their insights can help navigate enduring challenges in digital health.

Digital divide

Worldwide, the UN estimates that 3.8 billion people are offline and even in the US, 19 million people do not have reliable connectivity access. Other barriers to access include a lack of basic digital literacy required to use many digital health platforms. As a result, the already existing health gap between low-income and high-income populations may become further exacerbated by up and coming health technologies. To be effective, digital health solutions must foster the development of health literacy skills amongst platform users to make sure that the technology is used as intended

Bio-surveillance risks

In the age of the COVID-19 pandemic, the use of digital health platforms as a means to contain the spread of the disease has been accelerated worldwide. Governments in many economies, including South Korea, Taiwan, India, Italy, Poland, and China, have implemented strict digital track and trace systems to both identify those infected with COVID-19 and to ensure that they obey quarantine guidelines.

Although some studies (such as one by the Asian Development Bank) have suggests that such programs have been beneficial in combating spread, some critics worry have continued to express strong concerns about the potential loss of civil liberties associated with individuals handing over their private health data to government entities; this includes whether new or emergency regulations will stay in place in a post-pandemic world.

Additional Legal and Regulatory Issues

In the United States, the Health Insurance Portability and Accountability Act (HIPAA) of 1996 was the first comprehensive framework that aimed to protect the personal data of patients. In 2009, it was amended with the Health Information Technology for Economic and Clinical Health (HITECH) Act which seeks to examine personal health data privacy laws through the lens of the private sector and increase enforcement of HIPAA. Critics of these acts claim that they don't go far enough as there are still around 600,000 types of businesses that can access patient data without explicit consent. Not to mention, there are extensive reports proving that HIPAA regulations are constantly violated, making some wonder whether the government even has the capacity to enforce the laws that they put in place. With major companies like Facebook and Apple moving into digital health, critics question whether existing regulations are comprehensive enough.

Electronic Medical Records (EMRs)

Due to the initial gap between the expectations and performances of electronic medical records, they are frowned upon by clinicians. The initial failures have shaped physicians' perceptions of EMR. Therefore, before considering adopting the EMRs in the medical field, the quality of the information system has to be accounted for. Physicians that use the EMRs have a different view of how effective this new technology is and most of this has to do with age. Younger primary care physicians (PCP) find the technology easier to use as they have more knowledge about technology, therefore were inclined to use EMRs than older physicians with less knowledge of technology. Electronic medical records still have positive and negative implications for the medical field. Some of the positives of the EMRs in the medical field include the accuracy of results by both minimalizing the errors that used to occur as well as having more complete records. This leads to having a better quality of healthcare for patients because the guidelines are better followed. Not only that, but the efficiency of the work also increases because not only can the data be shared more readily, but also the time required to work on the medical records is less. However, there is contrary information which is that when it comes to data management and communication function, EMRs are less effective. Another positive is that there is better privacy for the records as they are harder to access by non-authoritative personnel. However, all these benefits are debatable because there is no tangible evidence that there has been an improvement in the quality of the work being performed by primary care physicians.

There are also negative consequences of using electronic medical records. Firstly, the place where the EMRs are being implemented would have to be financially capable as there is a very high cost of implementation. Additionally, the systems that are being used at the location would have to be modified so that the EMRs would be relevant and useful to the location. This implementation of EMRs would not be possible at locations that lack the resources to instruct physicians in charge of using the new E-health applications, especially in smaller or solo clinics. Not only that, but EMRs also are unable to factor in the social and psychological aspects of a patient into the record. To better understand how EMRs would compare with paper-based records in a hospital setting, a study was conducted between two hospitals and each of the hospitals adopted one of the methods. The results were that the quality of healthcare service in the hospital that had adopted the usage of EMRs was better than the other hospital. The quality of health care services is defined by how health results are improved. Multiple factors play a role in quality enhancement. Some factors are regarding the interaction between the patient and physician. For example, whether the patient gets assurance from the responses given by the physician.

Burden on healthcare providers' well-being

The integration of digital health has brought about considerable challenges for healthcare providers, and some physicians are highly critical of the utility of EMRs for patient care, and point to their rising use as a significant component in physician burnout. Other negative experiences and challenges encompass frustrations stemming from communication problems, reduced physician-patient interaction, inadequate resources, increased workloads, system complexity, difficulties in accessing information within Electronic Health Records (EHRs), and limited access to web-based information stored in digital systems. Additionally, clinicians often find themselves overwhelmed by the sheer volume of data and alerts generated by digital tools, which can hinder patient-centered care. In this digital healthcare landscape, emerging fears are prevalent, including the fear of change and potential job replacement, the fear of forgetting crucial patient information, and the fear of misinterpreting patient data. These fears contribute to increased stress and anxiety when new technologies are adopted. Furthermore, a sense of confusion is reported by some clinicians, stemming from a conflict between digital tools and their professional identity. This conflict revolves around concerns related to work visibility and perceived threats to professional autonomy.

Machine to machine

From Wikipedia, the free encyclopedia
https://en.wikipedia.org/wiki/Machine_to_machine

Machine to machine (M2M) is direct communication between devices using any communications channel, including wired and wireless. Machine to machine communication can include industrial instrumentation, enabling a sensor or meter to communicate the information it records (such as temperature, inventory level, etc.) to application software that can use it (for example, adjusting an industrial process based on temperature or placing orders to replenish inventory). Such communication was originally accomplished by having a remote network of machines relay information back to a central hub for analysis, which would then be rerouted into a system like a personal computer.

More recent machine to machine communication has changed into a system of networks that transmits data to personal appliances. The expansion of IP networks around the world has made machine to machine communication quicker and easier while using less power. These networks also allow new business opportunities for consumers and suppliers.

History

Wired communication machines have been using signaling to exchange information since the early 20th century. Machine to machine has taken more sophisticated forms since the advent of computer networking automation and predates cellular communication. It has been utilized in applications such as telemetry, industrial, automation, and SCADA.

Machine to machine devices that combined telephony and computing were first conceptualized by Theodore Paraskevakos while working on his Caller ID system in 1968, later patented in the U.S. in 1973. This system, similar but distinct from the panel call indicator of the 1920s and automatic number identification of the 1940s, which communicated telephone numbers to machines, was the predecessor to what is now caller ID, which communicates numbers to people.

The first caller identification receiver

Processing Chips

After several attempts and experiments, he realized that in order for the telephone to be able to read the caller's telephone number, it must possess intelligence so he developed the method in which the caller's number is transmitted to the called receiver's device. His portable transmitter and receiver were reduced to practice in 1971 in a Boeing facility in Huntsville, Alabama, representing the world's first working prototypes of caller identification devices. They were installed at Peoples' Telephone Company in Leesburg, Alabama and in Athens, Greece where they were demonstrated to several telephone companies with great success. This method was the basis for modern-day Caller ID technology. He was also the first to introduce the concepts of intelligence, data processing and visual display screens into telephones which gave rise to the smartphone.

In 1977, Paraskevakos started Metretek, Inc. in Melbourne, Florida to conduct commercial automatic meter reading and load management for electrical services which led to the "smart grid" and "smart meter". To achieve mass appeal, Paraskevakos sought to reduce the size of the transmitter and the time of transmission through telephone lines by creating a single chip processing and transmission method. Motorola was contracted in 1978 to develop and produce the single chip, but the chip was too large for Motorola's capabilities at that time. As a result, it became two separate chips (shown at right).

While cellular is becoming more common, many machines still use landlines (POTS, DSL, cable) to connect to the IP network. The cellular M2M communications industry emerged in 1995 when Siemens set up a department inside its mobile phones business unit to develop and launch a GSM data module called "M1" based on the Siemens mobile phone S6 for M2M industrial applications, enabling machines to communicate over wireless networks. In October 2000, the modules department formed a separate business unit inside Siemens called "Wireless Modules" which in June 2008 became a standalone company called Cinterion Wireless Modules. The first M1 module was used for early point of sale (POS) terminals, in vehicle telematics, remote monitoring and tracking and tracing applications. Machine to machine technology was first embraced by early implementers such as GM and Hughes Electronics Corporation who realized the benefits and future potential of the technology. By 1997, machine to machine wireless technology became more prevalent and sophisticated as ruggedized modules were developed and launched for the specific needs of different vertical markets such as automotive telematics.

21st century machine to machine data modules have newer features and capabilities such as onboard global positioning (GPS) technology, flexible land grid array surface mounting, embedded machine to machine optimized smart cards (like phone SIMs) known as MIMs or machine to machine identification modules, and embedded Java, an important enabling technology to accelerate the Internet of things (IOT). Another example of an early use is OnStar's system of communication.

The hardware components of a machine to machine network are manufactured by a few key players. In 1998, Quake Global started designing and manufacturing machine to machine satellite and terrestrial modems. Initially relying heavily on the Orbcomm network for its satellite communication services, Quake Global expanded its telecommunication product offerings by engaging both satellite and terrestrial networks, which gave Quake Global an edge in offering network-neutral products.

In the 2000s

In 2004, Digi International began producing wireless gateways and routers. Shortly after in 2006, Digi purchased Max Stream, the manufacturer of XBee radios. These hardware components allowed users to connect machines no matter how remote their location. Since then, Digi has partnered with several companies to connect hundreds of thousands of devices around the world.

In 2004, Christopher Lowery, a UK telecoms entrepreneur, founded Wyless Group, one of the first Mobile Virtual Network Operators (MVNO) in the M2M space. Operations began in the UK and Lowery published several patents introducing new features in data protection & management, including Fixed IP Addressing combined with Platform Managed Connectivity over VPNs. The company expanded to the US in 2008 and became T-Mobile's largest partners on both sides of the Atlantic.

In 2006, Machine-to-Machine Intelligence (M2Mi) Corp started work with NASA to develop automated machine to machine intelligence. Automated machine to machine intelligence enables a wide variety of mechanisms including wired or wireless tools, sensors, devices, server computers, robots, spacecraft and grid systems to communicate and exchange information efficiently.

In 2009, AT&T and Jasper Technologies, Inc. entered into an agreement to support the creation of machine to machine devices jointly. They have stated that they will be trying to drive further connectivity between consumer electronics and machine to machine wireless networks, which would create a boost in speed and overall power of such devices. 2009 also saw the introduction of real-time management of GSM and CDMA network services for machine to machine applications with the launch of the PRiSMPro™ Platform from machine to machine network provider KORE Telematics. The platform focused on making multi-network management a critical component for efficiency improvements and cost-savings in machine to machine device and network usage.

Also in 2009, Wyless Group introduced PORTHOS™, its multi-operator, multi-application, device agnostic Open Data Management Platform. The company introduced a new industry definition, Global Network Enabler, comprising customer-facing platform management of networks, devices and applications.

Also in 2009, the Norwegian incumbent Telenor concluded ten years of machine to machine research by setting up two entities serving the upper (services) and lower (connectivity) parts of the value-chain. Telenor Connexion in Sweden draws on Vodafone's former research capabilities in subsidiary Europolitan and is in Europe's market for services across such typical markets as logistics, fleet management, car safety, healthcare, and smart metering of electricity consumption. Telenor Objects has a similar role supplying connectivity to machine to machine networks across Europe. In the UK, Business MVNO Abica, commenced trials with Telehealth and Telecare applications which required secure data transit via Private APN and HSPA+/4G LTE connectivity with static IP address.

In the 2010s

In early 2010 in the U.S., AT&T, KPN, Rogers, Telcel / America Movil and Jasper Technologies, Inc. began to work together in the creation of a machine to machine site, which will serve as a hub for developers in the field of machine to machine communication electronics. In January 2011, Aeris Communications, Inc. announced that it is providing machine to machine telematics services for Hyundai Motor Corporation. Partnerships like these make it easier, faster and more cost-efficient for businesses to use machine to machine. In June 2010, mobile messaging operator Tyntec announced the availability of its high-reliability SMS services for M2M applications.

In March 2011, machine to machine network service provider KORE Wireless teamed with Vodafone Group and Iridium Communications Inc., respectively, to make KORE Global Connect network services available via cellular and satellite connectivity in more than 180 countries, with a single point for billing, support, logistics and relationship management. Later that year, KORE acquired Australia-based Mach Communications Pty Ltd. in response to increased M2M demand within Asia-Pacific markets.

In April 2011, Ericsson acquired Telenor Connexion's machine to machine platform, in an effort to get more technology and know-how in the growing sector.

In August 2011, Ericsson announced that they have successfully completed the asset purchase agreement to acquire Telenor Connexion's (machine to machine) technology platform.

According to the independent wireless analyst firm Berg Insight, the number of cellular network connections worldwide used for machine to machine communication was 47.7 million in 2008. The company forecasts that the number of machine to machine connections will grow to 187 million by 2014.

A research study from the E-Plus Group shows that in 2010 2.3 million machine to machine smart cards will be in the German market. According to the study, this figure will rise in 2013 to over 5 million smart cards. The main growth driver is segment "tracking and tracing" with an expected average growth rate of 30 percent. The fastest growing M2M segment in Germany, with an average annual growth of 47 percent, will be the consumer electronics segment.

In April 2013, OASIS MQTT standards group is formed with the goal of working on a lightweight publish/subscribe reliable messaging transport protocol suitable for communication in M2M/IoT contexts. IBM and StormMQ chair this standards group and Machine-to-Machine Intelligence (M2Mi) Corp is the secretary. In May 2014, the committee published the MQTT and NIST Cybersecurity Framework Version 1.0 committee note to provide guidance for organizations wishing to deploy MQTT in a way consistent with the NIST Framework for Improving Critical Infrastructure Cybersecurity.

In May 2013, machine to machine network service providers KORE Telematics, Oracle, Deutsche Telekom, Digi International, Orbcomm and Telit formed the International Machine to Machine Council (IMC). The first trade organization to service the entire machine to machine ecosystem, the IMC aims at making machine to machine ubiquitous by helping companies install and manage the communication between machines.

Applications

Commonplace consumer application

Wireless networks that are all interconnected can serve to improve production and efficiency in various areas, including machinery that works on building cars and on letting the developers of products know when certain products need to be taken in for maintenance and for what reason. Such information serves to streamline products that consumers buy and works to keep them all working at highest efficiency.

Another application is to use wireless technology to monitor systems, such as utility meters. This would allow the owner of the meter to know if certain elements have been tampered with, which serves as a quality method to stop fraud. In Quebec, Rogers will connect Hydro Quebec's central system with up to 600 Smart Meter collectors, which aggregate data relayed from the province's 3.8-million Smart Meters. In the UK, Telefónica won on a €1.78 billion ($2.4 billion) smart-meter contract to provide connectivity services over a period of 15 years in the central and southern regions of the country. The contract is the industry's biggest deal yet. Some companies, such as M-kopa in Kenya, are using M2M to enforce a payment plan, by turning off its customers' solar devices remotely for non-payment. "Our loan officer is that SIM card in the device that can shut it off remotely," says Chad Larson, M-Kopa's finance director and its third co-founder, when describing the technology.

A third application is to use wireless networks to update digital billboards. This allows advertisers to display different messages based on time of day or day-of-week, and allows quick global changes for messages, such as pricing changes for gasoline.

The industrial machine to machine market is undergoing a fast transformation as enterprises are increasingly realizing the value of connecting geographically dispersed people, devices, sensors and machines to corporate networks. Today, industries such as oil and gas, precision agriculture, military, government, smart cities/municipalities, manufacturing, and public utilities, among others, utilize machine to machine technologies for a myriad of applications. Many companies have enabled complex and efficient data networking technologies to provide capabilities such as high-speed data transmission, mobile mesh networking, and 3G/4G cellular backhaul.

Telematics and in-vehicle entertainment is an area of focus for machine to machine developers. Recent examples include Ford Motor Company, which has teamed with AT&T to wirelessly connect Ford Focus Electric with an embedded wireless connection and dedicated app that includes the ability for the owner to monitor and control vehicle charge settings, plan single- or multiple-stop journeys, locate charging stations, pre-heat or cool the car. In 2011, Audi partnered with T-Mobile and RACO Wireless to offer Audi Connect. Audi Connect allows users access to news, weather, and fuel prices while turning the vehicle into a secure mobile Wi-Fi hotspot, allowing passengers access to the Internet.

Networks in prognostics and health management

Machine to machine wireless networks can serve to improve the production and efficiency of machines, to enhance the reliability and safety of complex systems, and to promote the life-cycle management for key assets and products. By applying Prognostic and Health Management (PHM) techniques in machine networks, the following goals can be achieved or improved:

• Near-zero downtime performance of machines and system;
• Health management of a fleet of similar machines.

The application of intelligent analysis tools and Device-to-Business (D2B) TM informatics platform form the basis of e-maintenance machine network that can lead to near-zero downtime performance of machines and systems. The e-maintenance machine network provides integration between the factory floor system and e-business system, and thus enables the real time decision making in terms of near-zero downtime, reducing uncertainties and improved system performance. In addition, with the help of highly interconnected machine networks and advance intelligent analysis tools, several novel maintenance types are made possible nowadays. For instance, the distant maintenance without dispatching engineers on-site, the online maintenance without shutting down the operating machines or systems, and the predictive maintenance before a machine failure become catastrophic. All these benefits of e-maintenance machine network add up improve the maintenance efficiency and transparency significantly.

As described in, The framework of e-maintenance machine network consists of sensors, data acquisition system, communication network, analytic agents, decision-making support knowledge base, information synchronization interface and e-business system for decision making. Initially, the sensors, controllers and operators with data acquisition are used to collect the raw data from equipment and send it out to Data Transformation Layer automatically via internet or intranet. The Data Transform Layer then employs signal processing tools and feature extraction methods to convert the raw data into useful information. This converted information often carries rich information about the reliability and availability of machines or system and is more agreeable for intelligent analysis tools to perform subsequent process. The Synchronization Module and Intelligent Tools comprise the major processing power of the e-maintenance machine network and provide optimization, prediction, clustering, classification, bench-marking and so on. The results from this module can then be synchronized and shared with the e-business system on for decision making. In real application, the synchronization module will provide connection with other departments at the decision making level, like Enterprise Resource Planning (ERP), Customer Relation Management (CRM) and Supply Chain Management (SCM).

Another application of machine to machine network is in the health management for a fleet of similar machines using clustering approach. This method was introduced to address the challenge of developing fault detection models for applications with non-stationary operating regimes or with incomplete data. The overall methodology consists of two stages: 1) Fleet Clustering to group similar machines for sound comparison; 2) Local Cluster Fault Detection to evaluate the similarity of individual machines to the fleet features. The purpose of fleet clustering is to aggregate working units with similar configurations or working conditions into a group for sound comparison and subsequently create local fault detection models when global models cannot be established. Within the framework of peer to peer comparison methodology, the machine to machine network is crucial to ensure the instantaneous information share between different working units and thus form the basis of fleet level health management technology.

The fleet level health management using clustering approach was patented for its application in wind turbine health monitoring after validated in a wind turbine fleet of three distributed wind farms. Different with other industrial devices with fixed or static regimes, wind turbine's operating condition is greatly dictated by wind speed and other ambient factors. Even though the multi-modeling methodology can be applicable in this scenario, the number of wind turbines in a wind farm is almost infinite and may not present itself as a practical solution. Instead, by leveraging on data generated from other similar turbines in the network, this problem can be properly solved and local fault detection models can be effective built. The results of wind turbine fleet level health management reported in demonstrated the effectiveness of applying a cluster-based fault detection methodology in the wind turbine networks.

Fault detection for a horde of industrial robots experiences similar difficulties as lack of fault detection models and dynamic operating condition. Industrial robots are crucial in automotive manufacturing and perform different tasks as welding, material handling, painting, etc. In this scenario, robotic maintenance becomes critical to ensure continuous production and avoid downtime. Historically, the fault detection models for all the industrial robots are trained similarly. Critical model parameters like training samples, components, and alarming limits are set the same for all the units regardless of their different functionalities. Even though these identical fault detection models can effectively identify faults sometimes, numerous false alarms discourage users from trusting the reliability of the system. However, within a machine network, industrial robots with similar tasks or working regimes can be group together; the abnormal units in a cluster can then be prioritized for maintenance via training based or instantaneous comparison. This peer to peer comparison methodology inside a machine network could improve the fault detection accuracy significantly.

Open initiatives

• Eclipse machine to machine industry working group (open communication protocols, tools, and frameworks), the umbrella of various projects including Koneki, Eclipse SCADA
• ITU-T Focus Group M2M (global standardization initiative for a common M2M service layer)
• 3GPP studies security aspects for machine to machine (M2M) equipment, in particular automatic SIM activation covering remote provisioning and change of subscription.
• Weightless – standard group focusing on using TV "white space" for M2M
• XMPP (Jabber) protocol
• OASIS MQTT – standards group working on a lightweight publish/subscribe reliable messaging transport protocol suitable for communication in M2M/IoT contexts.
• Open Mobile Alliance (OMA_LWM2M) protocol
• RPMA (Ingenu)
• Industrial Internet Consortium