We live in an age of relentless and accelerating change, driven by demographic, social, and economic evolution. Each day, there are more of us consuming the finite natural resources of the planet. Our impact on the planet is increasing through urbanization, energy utilization, waste production, and so on, and this impact is not without consequences. Levels of pollution are increasing in our environment, with corresponding effects on our health and well-being. From smog clouds in cities and pollution of our drinking water to simply being denied sufficient peace to sleep soundly at night, human activity has enormous impact on us and on our planet.
KeywordsWireless Sensor Network Sensor Technology Wireless Body Area Network Sensor Application Smart Sensor
For a successful technology, reality must take precedence over public relations, for Nature cannot be fooled.
—Richard P. Feynman, Physicist
We live in an age of relentless and accelerating change, driven by demographic, social, and economic evolution. Each day, there are more of us consuming the finite natural resources of the planet. Our impact on the planet is increasing through urbanization, energy utilization, waste production, and so on, and this impact is not without consequences. Levels of pollution are increasing in our environment, with corresponding effects on our health and well-being. From smog clouds in cities and pollution of our drinking water to simply being denied sufficient peace to sleep soundly at night, human activity has enormous impact on us and on our planet. Major changes in the way we work and live during the last century mean we are also living much more sedentary lifestyles. This has resulted in growing public health issues, such as obesity, arteriosclerosis, cancer, chronic liver disease, and other lifestyle diseases. Increased life expectancy places greater pressures on our healthcare systems as the world’s population continues to grow older. Governments are being forced to cut programs such as home healthcare assistance to reduce burgeoning costs. The current model simply does not scale into the future.
We also need to move our fundamental approach to healthcare from a reactive model to a wellness-oriented model. Here, the focus is on keeping people healthy for as long as possible with the least cost to the system. Providing people with actionable information about their health and the factors influencing it, either positively or negatively, is important. Systems that provide easy access to data on exercise, diet, ambient environment, and so forth, along with intelligent processing and presentation of the data, are critical to supporting sustainable behavior change. It is a world full of challenges and in need of solutions to address key global issues. Technologies such as sensors can give us the tools to help address many of the significant global challenges of the 21st century.
Sensors play an integral role in numerous modern industrial applications, including food processing and everyday monitoring of activities such as transport, air quality, medical therapeutics, and many more. While sensors have been with us for more than a century, modern sensors with integrated information and communications technology (ICT) capabilities—smart sensors—have been around for little more than three decades. Remarkable progress has been made in computational capabilities, storage, energy management, and a variety of form factors, connectivity options, and software development environments. These advances have occurred in parallel to a significant evolution in sensing capabilities. We have witnessed the emergence of biosensors that are now found in a variety of consumer products, such as tests for pregnancy, cholesterol, allergies, and fertility.
The development and rapid commercialization of low-cost microelectromechanical systems (MEMS) sensors, such as 3D accelerometers, has led to their integration into a diverse range of devices extending from cars to smartphones. Affordable semiconductor sensors have catalyzed new areas of ambient sensing platforms, such as those for home air-quality monitoring. The diverse range of low-cost sensors fostered the emergence of pervasive sensing. Sensors and sensor networks can now be worn or integrated into our living environment or even into our clothing with minimal effect on our daily lives. Data from these sensors promises to support new proactive healthcare paradigms with early detection of potential issues, for example, heart disease risk (elevated cholesterols levels) liver disease (elevated bilirubin levels in urine), anemia (ferritin levels in blood) and so forth. Sensors are increasingly used to monitor daily activities, such as exercise with instant access to our performance through smartphones. The relationship between our well-being and our ambient environment is undergoing significant change. Sensor technologies now empower ordinary citizens with information about air and water quality and other environmental issues, such as noise pollution. Sharing and socializing this data online supports the evolving concepts of citizen-led sensing. As people contribute their data online, crowdsourced maps of parameters such air quality over large geographical areas can be generated and shared.
Although all these advances are noteworthy and contribute meaningfully and positively to many people’s lives, a note of caution is also in order. As Richard Feynman points out, reality must take precedence over public relations. Sensors should not be regarded as a panacea for all our problems. Instead, they should be treated as highly useful tools. As always, the right tool is required for the right job and, like any complex tool, sensors and sensor systems have their strengths and weaknesses. Careful matching of the sensor and its operational characteristics to the use case of interest is critical. The data must be of the required accuracy with appropriate stability for the lifetime of the required application. Highly sensitive and accurate sensors are generally more expensive, however, and therefore the cost of the sensor should be weighed carefully against an application’s data quality requirement. Sensor technologies, particularly wireless sensor networks (WSNs) (see Chapter 4), offer a wide variety of capabilities. However, they can sometimes lack meaningful use cases grounded in real-world needs that have either a clear social or economic benefit. These technologies do not have a meaningful value unless they address a problem of real interest in an innovative manner, with performance equal or superior to existing solutions. Real and committed consumers of the data must also exist. Finally, any discussion of the potential cost benefits of using sensors, particularly WSNs, is usually relevant only after the necessary operational performance criteria for an application can be met.
Many challenges remain for sensor technologies, particularly in the consumer domain. However, we are confident that the range of opportunities that are emerging will ensure rapid evolution of their capabilities to address any gaps that currently exist. The 20th century heralded the wide-scale emergence of sensors based on a diverse range of sensing approaches. The 21st will be the century of their application—driven by the convergence of sensing and ICT that will influence many aspects of our lives, especially the domains discussed in this book.
What This Book Covers
In this book we explore a wide range of topics related to sensing, sensor systems, and applications for monitoring health, wellness, and the environment. The book targets clinical and technical researchers, engineers, students, and members of the general public who want to understand the current state of sensor applications in the highlighted domains. The reader should gain a full awareness of the key challenges, both technical and non-technical, that need to be addressed in the development of successful end-to-end sensor applications. We provide real-world examples to give the reader practical insights into the successful development, deployment, and management of sensor applications. The reader will also develop an understanding of the personal, social, and ethical impact of sensor applications, now and in the future. The book provides an application-based approach to illustrate the application of sensor technologies in a practical and experiential manner. It guides the reader from the formulation of the research question, through the design and validation process, to the deployment and management phases of a sensor application. The processes and examples used in the book are primarily based on research carried out by Intel or by joint academic research programs.
The subject of sensing has grown enormously over the last 30 years. Therefore, we focus our treatment of basic sensing principles primarily on the chosen application domains described in Chapter 2. Key topics include electrochemical, optical biosensors, and MEMS sensor technologies. The influence of ICT technologies over the same period has been significant and has fundamentally changed the way in which we use sensors in our lives. Chapter 3 deals with the key technologies that have influenced the evolution of the smart sensor and sensor systems. Chapter 4 covers the use of sensors from an architectural perspective. Architectures range from discrete sensors to wireless sensor networks covering large geographic areas to the Internet of Things, in which vast numbers of sensors are connected to the Internet contributing to the creation of “big data”. We review the entire spectrum, from discrete sensors that might be used by an individual to sensor networks that are deployed over wide geographical areas. We also discuss the growing role of sensors in machine-to-machine applications.
A sensor is only as valuable as the data it can produce—so, ensuring quality is key for any sensor application. The way we present and consume sensor data can significantly influence its value, too. Processing, visualizing, and adding vibrancy to sensor data is discussed in Chapter 5. Regulatory considerations are dealt with in Chapter 6, particularly in the context of the application domains covered in this book. The ability to sense key aspects of our health and well-being is having a growing influence on society with both positive and in sometimes case negative consequences. Chapter 7 is primarily concerned with these influences and potential impacts from a social science perspective. A key challenge with sensor technologies is translating promising laboratory prototypes into real-world deployments. Chapter 8 looks at important aspects of planning and deploying sensors in real-world settings. Chapters 9, 10, and 11 outline the current applications of sensor technologies in monitoring the health, wellness, and environmental domains, analyzing the key drivers and inhibitors in the respective domains. We focus on the main emerging-technology practices, such as the role of mobile platforms like smartphones and tablets. Examples of practical solutions and innovative products appear throughout these chapters together with a view of how solutions in these domains will evolve in the future. Chapter 12 looks at how the early pioneers are building a vision of a new model of medicine in the 21st century. This vision is based on use of sensor technologies to provide continuous monitoring of the human body to provide a better understanding of its complexities and the influence of factors such as lifestyle, genetic make-up, the quality of the environment, and so on. It is a future where a visit to the doctor will no longer automatically result in a prescription for drugs to treat an aliment but rather one where doctors will prescribe patients with sensors and apps to diagnose the root cause of their health problems. We also look at the key trends that will influence the evolution of sensor applications in the future, such as the evolving use of crowdsourcing approaches, particularly in environmental applications.
A Brief History of Sensors
Sensing in the healthcare domain has been, until recently, restricted primarily to use in hospitals, with limited adoption outside this environment. Developments in both technology and care models are supporting adoption by patients, in-home care providers, public authorities, and individuals who want to proactively manage their health and wellness. For example, the concept of biosensing was first proposed by Clarke and Lyons in 1962. The concept of the glucose biosensor was brought to commercial reality in 1975 by the Yellow Springs Instrument Company. Biosensors have rapidly evolved in the intervening years to the point where they are a multi-billion dollar industry. They are now found in a wide variety of over-the-counter health-related applications, such as those for home testing AIDS or pregnancy, and for allergy detection, to mention just a few. More recently, biosensors are being used in the environmental domain for applications that, for example, detect bacteria, pesticides, and heavy metals in water samples.
The development of MEMS-based sensors led to the availability of small, accurate sensors at a price point that made it feasible to integrate them into a wide variety of devices ranging from sports watches to consumer electronics to cars. MEMS have become a key building block for many of the application domains discussed in this book. In 1959, Richard Feynman gave an insightful lecture at the California Institute of Technology called “There is Plenty of Room at the Bottom.” In this lecture he outlined the basic concepts and techniques for MEMS devices. However, it wasn’t until the early 1990s that U.S. government agencies started large programs that drove rapid acceleration in the development of MEMS sensors. Using semiconductor manufacturing techniques, the first surface micromachined accelerometer (ADXL50) was sold commercially by Analog Devices in 1992. This was followed in 1998 with MEMS-based gyroscopes from Bosch for commercial applications in the automotive sector (Marek et al., 2012). The availability of low cost, accurate, and reliable motion sensors has spawned a variety of applications, including those targeted at the health and wellness domains.
In recent decades the evolution of sensors has been strongly influenced by ICT technologies, with integration of microcontrollers, wireless communications modules, and permanent data storage. These technologies have supported the development of sensor systems with common architectures. Computing, storage, and communications features are used to serve multiple sensors with common connectivity. Collectively these enhancements have produced smart sensors that allow the delivery of intelligent sensor solutions with key features such as digital signal processing and wireless data streaming. In the health and wellness domain, wireless body-worn networks appeared around 1995. These networks—commonly referred to as wireless body area networks (WBAN)—comprise several sensors that measure physiological signals of interest and make that data available wirelessly to a computing device.
How will sensors continue to evolve? A number of key trends are emerging. First, we are starting to see the consumerization of sensors. There is a clear transition from limited, specialized use of sensors to greater general use among the public. Commercial sensor products can be found with greater frequency in pharmacies, sports stores, supermarket chains, and, of course, online. Adoption is rapidly growing in sports and wellness applications, with significant brands staking claims on the market and fueling its growth. The first personal environmental monitoring products have also emerged, with a focus on improving well-being. Crowdsourcing of data, though still in its infancy, is being driven by sensors either connected to smartphones or tablets or integrated into them, and by apps, and by connectivity to the Web or cloud. Continuous miniaturization of sensors and low-cost systems on chips (SOCs) will continue to fuel future development of the Internet of Things (IOT). Sensors will fade into the background of everyday life, and interaction with them will become passive and routine. The nexus of health, wellness, and environmental monitoring will continue to evolve and drive changes in human behaviors. Monitoring enabled by sensors will raise our awareness of how lifestyle choices and external influences impact our personal health and well-being. The adoption of data mining, particularly pattern-matching and machine-learning techniques, will help unlock the hidden patterns and associations in sensor data. These trends could give us the first glimpses of collective intelligence in which epidemiological insights may be possible with customizations for personalized health.
Drivers for Sensor Applications
As mentioned, a variety of social, economic, and environmental challenges are having a global impact. Changes in worldwide demographics have sparked significant debate on how to deliver effective healthcare in the 21st century that is affordable and sustainable. Technology, including sensing, has been an integral part of these discussions. Public health challenges due to the increase in lifestyle-related diseases such as obesity, once the preserve of Western nations, are gaining a foothold across the world. The industrialization of the planet over the last two centuries has had a profound effect on the quality of our environment. In the same period, the capacity of human activities such as transport to impact our environmental has grown substantially. There is a growing realization that the integral nature of our environment can significantly influence health and well-being. Solutions using sensor technologies allow people to be better informed by empowering them with information about the quality of the environment and its influence on them. Let us now look at some of these key drivers in more detail.
Health and Fitness
Lifestyle-related illnesses, resulting from lack of exercise, poor diet, smoking, and excessive alcohol consumption, are on the rise globally. A recent publication in the Lancet medical journal estimates that as many as 5.3 million of the 57 million deaths worldwide in 2008 could be a result of physical inactivity, and that increasing physical activity could increase the life expectancy across the globe by 0.68 years (Lee et al., 2013). Analysis of the Framingham heart study also provides evidence that physical activity conveys long-term beneficial effects by providing a protective effect against incidences of cardiovascular disease (Shortreed et al., 2013). Current guidelines recommend about 150 minutes of physical activity each week for adults. However, almost one-third of adults do not get enough physical activity, leading to greater risk of diseases such as heart disease and diabetes (Park, 2012).
Our diets have also changed significantly over the last century. With each passing decade, the consumption of processed foods and fast foods continues to rise globally, resulting in an increased intake of fat, salt, sweeteners, and simple sugars. There has also been significant growth in the consumption of meat and a decrease in the consumption of non-citrus fruits, vegetables, and whole-grain foods. Collectively these changes significantly increase the number of calories we consume, leading to rising obesity levels, among other issues. Patterns of alcohol consumption also changed in this period. The World Health Organization (WHO)has estimated that 2.5 million people die annually from the harmful consumption of alcohol (WHOa, 2011). Although average per capita consumption of alcohol in many countries of the Western world has either stabilized or fallen over the last few decades, it has risen significantly in other countries, such as India. The distribution of alcohol consumption within populations has become a major societal issue. For example, it has been found that 20 percent of the United States population is responsible for 90 percent of the alcohol consumption. Similar patterns exist in other countries, such as the Netherlands, China, and Canada. Binge drinking (consumption of five or more drinks), especially on weekends, has become common. This type of drinking can cause acute health problems, such as induced coma, respiratory depression, neurological damage, and more. (Babor, 2010). Smoking remains the single biggest cause of preventable disease (American Lung Association, 2013). Rates of smoking have remained largely unchanged over the last couple of decades. It is estimated that smoking will result in 450 million deaths between 2000–2050 (Jha, 2009). These lifestyle choices result in significant disease burdens and economic impact on our healthcare systems (Al-Maskari, 2010).
Illnesses such as cancer, cardiovascular disease, and diabetes have become the leading causes of death and disability globally (UNa, 2010). The Global Burden of Disease Study points out that growing numbers of young and middle-aged adults are developing noncommunicable diseases, such as cancer, that are driven by smoking, alcohol use, and obesity. For example, the prevalence of obesity in the Western world is 20–30 percent and increasing. As Asian countries adopt Western lifestyles and diets, obesity is increasing in countries such as China and India. Obesity is associated with elevated blood glucose levels, increased blood lipids (hyperlipidemia), high blood pressure, and decreased sensitivity to insulin. The WHO estimates that being overweight or obese is globally the fifth leading risk for death, resulting in at least 2.8 million adult deaths annually. It estimates that more than 500 million people are obese around the world (WHOb, 2013). For individuals who are already obese, regular monitoring of key factors such as blood pressure, blood glucose levels, heart rate, and blood lipids, helps to improve management of the disease. Sensor technologies can play a role in supporting the monitoring of these parameters either in community settings or in the home.
A more significant driver for sensor technology utilization is the growing trend in fitness. People are becoming more aware of how lifestyle can affect their health, thanks especially to high visibility public health campaigns. Individuals are motivated by a desire to manage their weight and maintain a sufficient level of fitness for a healthy lifestyle. Other individuals who are already overweight may want to take corrective actions to reduce their weight and improve their fitness levels. Insurance companies are also playing a role by offering premium discounts to individuals who adopt and maintain healthier lifestyles. And some employers have put programs in place to encourage employees to live more active lifestyles, with the benefit of reduced sick days and health insurance premium savings.
A variety of fitness technologies are now available to consumers, ranging from standalone sensing devices, such as pedometers, to apps for use with smartphones, to sports watches with integrated sensors. Also, computer game platforms, such as the Nintendo Wii, Microsoft Kinect, and PlayStation Move, now feature fitness games that use sensing. Many consumer electronics devices such as smartphones and MP3 players have integrated sensors and other features such as a GPS that can be used for fitness applications. The combination of sensing and other technologies can let people monitor and either maintain or improve their fitness levels on a day-to-day basis. There are also fitness developments among older adults, with a growing focus on encouraging participation in sports and similar physical activities. Improvements in muscle strength, balance, endurance, and so forth play a key role in allowing older adults to maintain their independence longer and slow or prevent the onset of frailty. Currently, this group is not among those adopting sports-sensing technologies; however, this is likely to change in the future. Greater convergence between health and wellness monitoring will play a significant role in adoption.
Global aging and the associated impact on healthcare systems have been well-documented. As a result of medical advances, better management of communicable diseases, and improved diet, people are living longer. The U.S. Census Bureau predicts an average increase in life expectancy between 1970 and 2020 of 12.2% (70.8 to 79.5 years). Conservative estimates place the increase in life expectancy during the course of the 21st century at 13 years (Fogel, 2011). The UN estimates that, globally, life expectancy will increase from 68 years in 2005–2010 to 81 in 2095–2100 (UNb, 2011). Others argue that the increase could actually be much larger. While there is debate over the exact increase in life expectancy during the 21st century, everyone agrees that we will live longer and that the increase in life span will have significant implications for our society.
Many countries, particularly Western ones, are suffering from an aging population. In this process, older adults become a proportionally larger share of the total population. The number of people aged 65 or older is projected to grow from an estimated 524 million in 2010 to nearly 1.5 billion in 2050. One interesting consequence of this growth is that by 2020 the number of people over 65 will outnumber children aged 5 or younger. This will be a first for humankind (WHOc, 2011). This demographic transition results in rising demands for health services and higher expenditures because older people are normally more vulnerable to health issues, including chronic diseases. This increased expenditure on public healthcare services is a growing concern for many governments.
Various efforts to address the increased level of expenditure have been tried and evaluated. Central to many efforts has been the use of ICT technologies, including sensors to deliver new, more affordable models of care in community and home locations. Sensors can monitor the key health indicators of a person directly or indirectly through ambient monitoring of daily patterns. In many respects, at-home healthcare is becoming part of the IOT. Initial deployments of technologies have been somewhat static and tied to the physical location of the person under observation. The near future will see small, wearable sensors that can monitor a person’s vital signs 24/7. An alert can be sent to a clinician when a certain limit is exceeded or when an abnormal event, such as someone collapsing and being unable to get up, is detected. These types of sensor technologies are fundamental to making health affordable and scalable to address the transition in global demographics.
As we have pointed out, the economics of healthcare is already under considerable strain due to changes in global demographics. Costs continue to climb, with a consequent need to shift the focus away from reactive treatment and toward proactive healthcare. This model encompasses prediction, diagnosing, and monitoring using various data sources. A cornerstone of this shift is the development of personalized medicine. In this model we move away from a population-level epidemiological approach to small groups or individuals defined by their biochemistry and genetics. Currently this information is beginning to be used to select the most appropriate drugs to treat diseases such as cancer. As the next generation of drug therapies emerge that target specific disease pathways, it is important to know the genetic profile of a patient to see whether he or she will respond to a particular drug therapy. This in turn is generating a growing demand for diagnostic tests that provide clinicians with specific information about the biology of the patient as well as disease-specific information, such as the cellular profile of a tumor. The need for a companion diagnostic test to accompany a therapy has already emerged in cancer treatments. For example, Genentech’s Herceptin targets breast tumor cells that exhibit significant amounts of the Her2/neu protein on their cell membranes. Testing for this protein in all new breast cancer tumors to determine if they can be treated by Herceptin has been specified by the National Comprehensive Cancer Network in the U.S. These tests represent both diagnostics and subsequent treatment monitoring opportunities for the biosensor industry.
These targeted treatments are a significant step forward in disease treatment but they are still reactive in nature. The future of personalized healthcare will be about using sensor technologies to establish and monitor biological norms and quickly identify deviations from them. We are starting to see the emergence of health maps constructed by proactive individuals that capture and document their health metrics on a longitudinal basis. Wired magazine, in an article entitled “Know Thyself: Tracking Every Facet of Life, from Sleep to Mood to Pain, 24/7/365,” discusses the utility of health-related metrics. The article describes how data can be used to create a personal macroscope to link a variety of data into a larger, readable pattern (Wolf, 2009). In this way we may be able to intervene to prevent a disease from occurring or to begin treatment at the earliest possible juncture to maximize efficacy, minimize long-term impact, and keep costs to a minimum. The combination of sensor and ICT technologies will cause medicine to morph. The tools to start this monitoring process for the motivated few already exist. This form of monitoring will become the norm, representing a major driver both for the development and adoption of sensor technologies into our everyday lives.
We should be cautious not forget the role sustainable behavior change has to play in the area of personalized healthcare. Aside from clinical diagnostic applications, it is ultimately the decision of individuals how they use the data provided by sensor technologies and what steps if any they take in modifying their behaviors and lifestyles. The ICT software tools provided with sensors can play a vital enabling role in supporting individuals. As individuals move along the path of behavior change, the manner in which the sensor data is visualized, information is personalized, goals are set, and on-line community supports are structured needs to continuously re-engage the individual over the long term. Behavior change of this nature is not a sprint but a marathon that for some will go on over a lifetime. ICT technologies that are static may have short-term impact but will suffer failure in the longer term. Successful solutions will place the sensing and supporting technologies around the needs of individuals in a manner that is highly personalized and supportive and evolves with the individual and their needs.
Healthcare spending is regularly near the top of the political agenda in most countries. It will account for 20–30 percent of GDP in some economies by 2050, a figure that is economically unsustainable (McKinsey, 2010). We have seen that this rapid increase in expenditure is driven by multiple factors, such as aging demographics, increasing prevalence of lifestyle illnesses, environmental factors, and so on. Public health policies are shifting away from reactive models of healthcare to preventative ones with a focus on wellness. Authorities see smarter healthcare as a means of maintaining quality while reducing delivery costs. Health and well-being are increasingly being positioned by public health authorities as an integral part of improving quality of life. More and more, public health bodies are becoming consumers of sensor technologies. At present, the most common applications of interest are home management of chronic disease patients and monitoring the well-being of older adults in their own homes.
There is also growing interest in the deployment of rehabilitation applications such as those required by patients recovering from surgery, for example joint replacements or stroke sufferers. Commercial applications targeting these patient groups are already available from companies like Telefonica and Philips. Additionally, systems are supporting the delivery of in-home exercise programs to improve strength and balance in older adults as a preventative measure against health concerns such as falls. Initial trials of telehealth solutions have had mixed results to date. A recent publication in the Lancetthat analyzed the effectiveness of the whole systems demonstrator program for telehealthcare in the UK, one of the largest studies of its kind, found it to be ineffective based on the cost of outcomes when compared to care-as-usual models (Henderson et al., 2013). Most issues identified in these trials are not technology related, however. Structural reform of medicine will be required to fully embrace the value of these technologies in treatment and care options. Although many studies into telehealth deployments indicate that the lack of acceptance of this new way of working is a key barrier to adoption, little progress has been made to date in developing solutions that can be implemented by front-line staff (Brewster et al., 2013).
This focus on health and well-being in our personal lives by the public health domain has also generated opportunities for companies not in the clinical sensing-technologies domain. Companies are considering public health opportunities by strengthening their brand value and repositioning their products. Opportunities include activity monitoring, calorie-intake tracking, fitness evaluation through vital-signs monitoring, and so on. Many product offerings intersect with key public health messages on exercise and activity, managing diet, and detecting early signs of health-related issues. These messages will be amplified as governments struggle with healthcare budgets in the future, creating more opportunities for sensor-related products.
Another key challenge facing healthcare services in the future will be a shortage of physicians to meet growing demands. The Association of American Colleges has estimated a potential shortfall of up to 124,000 physicians in the U.S. by 2025 (Dill et al., 2008). This shortage will inevitably require changes to the way healthcare is delivered. There will likely be a greater emphasis on the roles of nurse practitioners and physician assistants to deliver standardized protocols through the use of technology. Sensors will play a key role in such clinical tools, with intelligent software applications providing a layer of interpretation to support these practitioners. Examples of this approach are presented in Chapter 8.
As we will see throughout this book, sensors have evolved beyond being just “dumb” sensing devices to become smart sensors or sensor systems through the integration of ICT technologies. These capabilities have allowed sensors to participate in the larger technology ecosystem. We have now reached a technology nexus that is driving the rapid adoption of sensors technologies. Over one billion smartphones have been sold (Reisinger, 2012) and smartphone purchases exceeded that of standard mobile phones for the first time in 2013 (Svensson, 2013). 3G mobile broadband connectivity is widely available, particularly in urban areas, with faster 4G broadband services being rolled out. Connectivity, whether 3G or 4G, General Packet Radio Service (GPRS), Wi-Fi, or Bluetooth, is becoming pervasive. Cloud-based technologies are providing ever-increasing data storage, processing, aggregation, visualization, and sharing capabilities. Social media gives us a mechanism to crowdsource (sensor) data, to share this data, and to derive information from the data among Internet communities. Visionary technologist evangelists are already defining and creating a new future for medicine and healthcare by using sensors and ICT technologies to provide insights into the human body that were not previously possible. In his book The Creative Destruction of Medicine: How the Digital Revolution Will Create Better Health Care, Eric Topol describes how we are in the midst of a perfect digital storm. Super-convergence in the form of sensors and ICT technologies is the “start of illuminating the human black box” (Topol, 2012). Clinicians now have access to tools that will allow them to move toward a model of patient care based on predictive, preventive, and personalized medicine. The convergence of sensor and ICT technologies will give consumers an incredible capacity to generate information about their health and well-being and to participate in the management of their own healthcare with their clinicians. It will also allow them to control and exploit that information in a manner that would not have been previously possible. Sensing, social networking, smartphones, and connectivity will have a profound effect on medicine.
It is important to acknowledge the rapid advancements made in sensor technologies over the last thirty years. Biosensors and MEMS-based sensors have developed from essentially nothing in that timeframe to pervasive availability in a vast array of products. Biosensors have been a key cornerstone in the development of the consumer sensor market, driven by their relative low cost and reasonable accuracy. This market will continue to grow significantly as people take greater personal ownership of their health, driven by many of the factors discussed in this chapter. As the cost of MEMs-based sensors continues to fall, they can be found with ever-greater frequency in consumer electronics. This has led to the rapid growth of health- and wellness-related applications based around these sensing capabilities. As we embrace the data-driven society in our daily lives, demand for personal health metrics will continue to grow.
The threat of terrorism remains a constant source of concern for government and security agencies. Threats from terrorism have now evolved to include potential attacks from chemical, biological, radiological, and nuclear (CBRN)sources. Chemical threats involve the potential use of highly toxic industrial chemicals (for example, methyl isocyanate) or poisonous nerve agents (such as Sarin). Biological threats include the airborne release or introduction into water supplies of weaponized biological agents such as anthrax. Nuclear and radiological attacks pose a significant threat, particularly in urban areas. Large numbers of people could be exposed to radioactive contamination from so-called dirty bombs—non-fissile explosions of radioactive material released into the atmosphere.
Constant monitoring and vigilance is therefore required to prevent these forms of attack from occurring. Laboratory-based detection of agents offers excellent sensitivity and selectivity. However, national analytical laboratories are normally geographically removed from the threat location, resulting in significant delays in detection. Flexible in-field detection in the form of sensors is vital to continually provide information about a potential CBRN situation. Sensing capabilities that are available any time, any place to support the detection, identification, and quantification of CBRN hazards are a key requirement. Sensors are necessary to detect threats in air and water, and on land, personnel, equipment, or facilities. They are also required to detect these threats in their various physical states, whether solid, liquid, or gas. Ongoing threats will continue to drive the development of sensing technologies in the chemical and biological domains to improve the sensitivity and flexibility of detection of known agents. New sensor technologies will also be required as new forms of threat emerge in the future. For example, in the environmental domain, sensor technologies will be required to provide continuous monitoring of water sources and air quality to ensure their integrity and to immediately identify possible releases of chemical and biological agents. A variety of new biosensing and optical sensor technologies are in development that hopefully will be able to identify of the many current threats. This will allow authorities to react with greater speed than is currently possible.
The Internet of Things
The IOT is rapidly becoming a reality that surrounds us and intersects with many aspects of our lives. Pervasive connectivity and advances in ICT technologies have made possible the connection of more and more devices to the Internet. This is leading to a new wave of applications that have the potential to dramatically improve the way people live, learn, work, and entertain themselves. Sensors play a key role in connecting the physical world (temperature, C02, light, noise, moisture) with the digital world of IOT. Availability of this data can make us more proactive and less reactive in our interaction with the world around us (Evans, 2011).
The IOT is the next evolution of the Internet. The success of IOT will be driven by applications that deliver tangible improvements to people’s everyday lives. Sensors are likely to play a central role in providing the data streams upon which these applications can be built. For example, mobile and home-based environmental monitors allow people to track ambient air quality. They can use this data to either modify their environment or alter their behavior in order to maintain their health and wellness. As the value and impact of these applications reach widespread public visibility, the need for both improved and new sensor technologies is likely to grow rapidly.
Water and Food
The pressure on water and food resources will grow during the course of this century. A new lexicon has emerged around water. Terms such as water scarcity, water stress, water shortage, water deficits, and water crisis have now entered public consciousness in many parts of the world. Various estimates put the number of people affected by water shortages as 3.1 to 4.3 billion people by 2050 (Gosling et al., 2013). A recent article in the Guardian newspaper paints an even more dramatic picture by suggesting that within two generations, most people on the planet will experience water shortages (Harvey, 2013). In the U.S., the Southwest states of Arizona and Texas and the Midwest states of Kansas and Nebraska in particular are facing severe freshwater shortages (Stockdale et al., 2010)(Koch, 2010). Countries such as China (Economist, 2013) and India (Duxfield, 2013) and regions of Africa, the Middle East, and Asia are already experiencing water shortages that are likely to lead to local and regional tensions (Waslekar, 2012, Connor, 2013). The UN has estimated that the world’s population will grow to 8.1 billion by 2025 (Lederer, 2013), driven by high birth rates in the developing world and increased life expectancy. These population changes will further increase pressure on dwindling water resources in many areas.
Stewart Patrick, in his article “The Coming Global Water Crisis,” identifies a number of other key contributors to the water crisis in addition to climate change. The global population is becoming increasingly urbanized, leading to rises in personal consumption, sanitation needs, and public infrastructure expenditures. Changes in dietary preferences as the global middle class expands will have a significant impact on the amount of meat consumed. This will result in increased livestock rearing, which is a water-intensive activity (Patrick, 2102). Water management is extremely poor in most parts of the world. Even where it does exist, particularly in the Western world, the infrastructure is antiquated with as much as 50 percent of water being lost through leakage. The development of smart water grids with integrated sensing capabilities is gaining prominence among utilities and government organizations. Sensors will provide detection of leakages, as well as the identification of water quality issues such as treatment problems or pollution. Sensors have the potential to help improve the sustainability of water resources through better management and protection. This will require continued evolution of sensors to deliver laboratory analytical capabilities in-situ on a 24/7 monitoring basis to protect this valuable resource. We will also see innovations in how we produce our fresh drinking water, such as chemical-free production and waste-water treatments. These innovations will require sensor technologies to provide continuous monitoring in order to ensure water quality from both human health and environmental perspectives.
In the agricultural domain, water use is enormously inefficient, particularly with respect to irrigation practices. The UN has identified that use of water for irrigation represents almost 70 percent of the total withdrawn for human uses. In comparison, industry represents 20 percent and municipal use about 10 percent (UNc, 2013). Currently, irrigation regimes are typically schedule-based, with no system intelligence. The use of sensors to provide soil moisture measurements, combined with ambient environmental monitoring and crop-specific parameter monitoring, will enable intelligent crop irrigation. This will help to reduce water consumption while maintaining or improving crop yields.
Consumers driven by health concerns adopting sensor technologies to test the quality of their drinking water and food will become a growing trend. People are becoming more aware of the types and sources of their food. Health-conscious consumers have embraced, among other things, organic foods. Sensors to identify whether a food is organic are now commercially available. Consumer-oriented sensors that measure common aspects of water quality are also emerging. The sensor data can be easily shared online to support crowdsourced knowledge-sharing. This will allow people to make informed decisions and to advocate for change or improvements in their water and food supplies as necessary.
There are many potential factors surrounding us on a daily basis that can affect our wellness or directly influence the development of illness. The effects of poor water and air quality, pathogens in the food supply, and noise and light pollution will continue to have significant health impacts. Increased urbanization, growing use of motor vehicles and other forms of transport, increased waste production (human, animal, and industrial), and other factors will increase pressure on our natural environment. The effects of these are clearly visible in many large cities in the form of poor air quality. Smog clouds, common in many large cities, can have a dramatic effect on people suffering from respiratory issues, such as chronic obstructive pulmonary disease (COPD) and asthma. Exposure to fumes, gases, or dust in the workplace is estimated to be responsible for 11 percent of asthma cases globally (WHOd, 2007). The number of asthma sufferers continues to grow on a global basis. In the U.S., about 1 in 14 had asthma in 2001; that number had increased to 1 in 12 by 2009 (AAAAI, 2013). People are now turning to sensor technologies to better understand the relationship between parameters such as air quality and their health.
Institutional environmental monitoring, particularly of air quality, does provide us with insight into the quality of the environment. However, this form of monitoring can lack geographical granularity and a level of interactivity that people expect or require. Commercial sensor technologies now starting to emerge that empower people to track the air quality of their home environments and other areas they frequent. Other sensor-based applications are emerging that can be used to identify and track areas of high pollen and dust that affect people suffering from asthma and other respiratory conditions. This information allows suffers to make decision such as adjusting their route to work or school to avoid areas that might affect their condition. Although many of these applications are in development or are relatively new to the market, interest is already significant. Development of these of technologies and products will see strong growth over the next decade. Growth will be driven by changes in attitude toward environmental awareness as sensor technologies make it much more tangible. Personal perspectives will move from general awareness to a more personal outlook. This personal perspective will encourage greater interactivity with sensor data and modification of living environments to improve levels of wellness. Data will be shared and analyzed via the Web and the cloud as individuals endeavor to understand what the data is telling them, by using the collective intelligence of online communities and engaging in informed speculation on what the data is inferring about potential future impacts. These activities will mirror in many ways what is already happening in the health and wellness domains. It is also likely that over time greater overlap in these domains will occur as individuals and groups endeavor to build an understanding of how the quality of their environment such as their home impacts on their personal health and wellbeing.
Challenges for Sensor Applications
The drivers for sensor applications are significant and will continue to grow. Evolution of existing sensor technologies and development of new ones will continue to deliver new, innovative applications. The demand is there and growing—but can sensor technologies deliver on the promise? We must be careful to not equate demand with delivery without evidence. It has been pointed out that scanning the Internet, literature, and popular commentary can give the impression that fully functional sensor solutions are available to meet our needs (McAdams et al., 2012). We must be careful not to conclude that sensors are a panacea for all our needs. The truth is more complicated.
It is important to disaggregate sensors into their respective architectures: standalone, body-worn wireless networks, and more general wireless sensor networks. Each configuration presents its own unique set of challenges, some of which are more significant than others. Across the three configurations, sensor data quality is a universal requirement. For body-worn applications, the sensor-human interface is typically challenging, with issues such as compliance, comfort, artifact introduction, and hygiene being some of the key issues that must be dealt with. For diagnostic applications, considerable regulatory hurdles may have to be addressed. Questions need to be asked about the accuracy of products that are focused on in-home testing without regulatory approval or independent certification.
With standalone sensors, ensuring the measurement of a representative sample can be challenging. The actual technology used in the sensor can also have significant influence on the quality and accuracy of the data. Whereas inexpensive sensors can increase affordability and access to data, this may come at the cost of data quality. In such cases, no sensor data may be better than inaccurate measurements, which can create a false sense of security or result in an unnecessary false alarm.
For wireless sensor networks, communications, power, cost of deployment, and remote manageability are a few of the key factors that influence the viability of WSN applications. The deployment of WSNs at scale (thousands of nodes) is a challenge that has not yet been addressed properly. Throughout this book we present the technical, social, and organizational challenges that accompany the adoption, deployment, and utilization of sensors. Although we acknowledge the fantastic capabilities of sensors, a sprinkling of reality must also apply. Armed with a balanced view of sensors, we can better set realistic expectations, utilize them appropriately, and set achievable evolutionary demands.
Sensors Enabling Innovation
Over the last decade there has been a growing emphasis on adding embedded intelligence to the world around us in order to make it smarter. This vision of smart encompasses cities, transport, energy, health, homes, and public buildings, among other areas. The goal of smarter environments and activities is driven by the complex mixture of challenges outlined in this chapter. We increasingly need creative solutions that can do more with less to meet these growing challenges. Innovation should be about bringing a great idea to market. For example, 60 percent of the world population will live in cities by 2020, creating enormous challenges in delivering sustainable living environments for those city dwellers.
It is interesting to note that the proliferation of these devices and services may well be driven by real-world virality. Social media and other forms on online engagement will spark conversations leading to public engagement. This type of engagement is already playing a greater role in shaping products and services. The smart aspects of our lives will contain a greater element of pull, rather than the push that has been the de facto approach to date. Smart sensors and services need to be insight-driven, prototype-powered, and foresight-inspired, particularly in the domains discussed in this book, as they have direct and tangible connection to human end users. It is important to maintain the balance requirements between the creative and analytical processes. We must ensure that needs are identified and appropriate insights collected to realize the opportunities in a way that makes sense from the perspectives of customers, science, engineering, and economics.
The continued technological evolution of sensors will see increasing levels of miniaturization. This is critical for embedded applications where limited form factor space (such as in a smartphone) is a constraint. Commercially viable sensor materials that can be integrated into items such as clothing will likely emerge. In the research domain, we see many interesting demonstrations of these materials. Innovative application of these materials will be central to bridging the gap between interesting research and commercial reality. Sensors will continue to become smarter, driven by ever- closer integration with ICT capabilities. This combination will provide an exciting platform for future innovation product and services.
Marek, Jiri and Udo-Martin Gómez, “MEMS (Micro-Electro-Mechanical Systems) for Automotive and Consumer ” in Chips 2020: A Guide to the Future of Nanoelectronics, Höfflinger, Bernd, Ed., Heidelberg, Springer-Verlag, 2012, pp. 293–314.
Lee, I-Min, et al., “Effect of physical inactivity on major non-communicable diseases worldwide: an analysis of burden of disease and life expectancy,” The Lancet, vol. 380 (9838), pp. 219–229, 2013.
Shortreed, Susan M, Anna Peeters, and Andrew B Forbes, “Estimating the effect of long-term physical activity on cardiovascular disease and mortality: evidence from the Framingham Heart Study,” Heart, vol. 99 (9), pp. 649–654, 2013.
Park, Alice. “Lack of Exercise as Deadly as Smoking, Study Finds”, Last Update: July 18th 2012, http://healthland.time.com/2012/07/18/lack-of-exercise-as-deadly-as-smoking-study-finds/ /2012/07/18/lack-of-exercise-as-deadly-as-smoking-study-finds/
WHOa. “Alcohol”, Last Update: February, 2011, http://www.who.int/mediacentre/factsheets/fs349/en/index.html
Babor, Thomas F., “Alcohol comsumption trends and patterns of drinking,” in Alcohol: No Ordinary Commodity: Research and Public Policy, Babor, Thomas, Ed., Oxford, UK, Oxford Press, 2010, pp. 23–42.
American Lung Association, “Smoking”, http://www.lung.org/stop-smoking/about-smoking/health-effects/smoking.html /stop-smoking/about-smoking/health-effects/smoking.html, 2013.
Jha, Prabhat, “Avoidable global cancer deaths and total deaths from smoking,” Nature Reviews Cancer, vol. 9 pp. 655–664, 2009.
Al-Maskari, Fatma, “Lifestyle Disease: An Economic Burden on the Health Services”, UN Chronicle - Achieving Global Health, vol. XLVII (2), 2010.
United Nationsc, “Global status report on noncommunicable disease”, http://www.who.int/nmh/publications/ncd_report_full_en.pdf , 2010.
WHOb. “Obesity and Overweight”, Last Update: March, 2013, http://www.who.int/mediacentre/factsheets/fs311/en/index.html
Fogel, Robert W. “Longer Lives and Lower Health Costs in 2040: Business Class”, Last Update: July 21st 2011, http://www.bloomberg.com/news/2011-07-21/business-class-longer-lives-and-lower-health-costs.html /news/2011-07-21/business-class-longer-lives-and-lower-health-costs.html
United Nationsa, “World Population to reach 10 billion by 2100 if Fertility in all Countries Converges to Replacement Level”, http://esa.un.org/unpd/wpp/Other-Information/Press_Release_WPP2010.pdf /unpd/wpp/Other-Information/Press_Release_WPP2010.pdf, 2011.
WHOc, “Global Health and Aging”, http://www.who.int/ageing/publications/global_health.pdf , 2011.
Wolf, Gary, “Know Thyself: Tracking Every Facet of Life, from Sleep to Mood to Pain, 24/7/365”, Wired, vol., 2009, http://www.wired.com/medtech/health/magazine/17-07/lbnp_knowthyself?currentPage=2 /medtech/health/magazine/17-07/lbnp_knowthyself?currentPage=2
McKinsey & Company, “mHealth: A new vision for healthcare”, http://www.mckinsey.com/Search.aspx?q=mHealth&l=Insights%20%26%20Publications /Search.aspx?q=mHealth%26l=Insights%20%26%20Publications, 2010.
Henderson, Catherine, et al., “Cost effectiveness of telehealth for patients with long term conditions (Whole Systems Demonstrator telehealth questionnaire study): nested economic evaluation in a pragmatic, cluster randomised controlled trial,” BMJ, vol. 346, 2013.
Brewster, Liz, Gail Mountain, Bridgette Wessels, Ciara Kelly, and Mark Hawley, “Factors affecting front line staff acceptance of telehealth technologies: a mixed-method systematic review,” Journal of Advanced Nursing, 2013.
Dill, Michael J. and Edward S. Salsberg, “The Complexities of Physician Supply and Demand: Projects Through 2025”, Association of Americian Medical Colleges (AAMC), 2008.
Reisinger, Don. “Worldwide smartphone user base hits 1 billion”, Last Update: October 17th 2012, http://news.cnet.com/8301-1035_3-57534132-94/worldwide-smartphone-user-base-hits-1-billion/ /8301-1035_3-57534132-94/worldwide-smartphone-user-base-hits-1-billion/
Svensson, Peter. “Smartphone now outsell ‘dumb' phones”, Last Update: April 29th 2013, http://www.3news.co.nz/Smartphones-now-outsell-dumb-phones/tabid/412/articleID/295878/Default.aspx /Smartphones-now-outsell-dumb-phones/tabid/412/articleID/295878/Default.aspx
Topol, Eric, The Creative Destruction of Medicine: How the Digital Revolution Will Create Better Health Care. New York: Basic Books, 2012.
Evans, Dave, “The Internet of Things - How the Next Evolution of the Internet Is Changing Everything”, Cisco, 2011.
Gosling, Simon N. and Nigel W. Arnell, “A global assessment of the impact of climate change on water scarcity,” Climatic Change, pp. 1–15, 2013.
Harvey, Fiona. Global majority faces water shortages ‘within two generations', The Guardian, http://www.theguardian.com/environment/2013/may/24/global-majority-water-shortages-two-generations /environment/2013/may/24/global-majority-water-shortages-two-generations, 2013.
Stockdale, Charles B., Michael B. Sauter, and Douglas A. McIntyre. “The Ten Biggest American Cities That Are Running Out Of Water”, Last Update: October 29th 2010, http://247wallst.com/investing/2010/10/29/the-ten-great-american-cities-that-are-dying-of-thirst/ /investing/2010/10/29/the-ten-great-american-cities-that-are-dying-of-thirst/
Koch, Wendy. Global warming raises water shortage risks in one-third of U.S. counties, USA Today, 2010.
The Econmist, “All dried up - Northern China is running out of water, but the government’s remedies are potentially disastrous”, http://www.economist.com/news/china/21587813-northern-china-running-out-water-governments-remedies-are-potentially-disastrous-all /news/china/21587813-northern-china-running-out-water-governments-remedies-are-potentially-disastrous-all, 2013.
Duxfield, Flint. “Irrigation depleting global water stores”, Last Update: July 10th 2013, http://www.abc.net.au/news/2013-07-10/nrn-dist-global-water-shortages/4811140 /news/2013-07-10/nrn-dist-global-water-shortages/4811140
Waslekar, Sundeep. “Will Water Scarcity Increase Tensions Across Asia”, Last Update: October 1st, 2012, http://www.forbes.com/2012/01/09/forbes-india-water-wars-across-asia.html /2012/01/09/forbes-india-water-wars-across-asia.html
Connor, Steve. Water shortage in Dead Sea could increase tensions in Middle East, The Independent, http://www.independent.co.uk/news/science/water-shortages-in-dead-sea-could-increase-tensions-in-middle-east-6273289.html /news/science/water-shortages-in-dead-sea-could-increase-tensions-in-middle-east-6273289.html, 2013.
Lederer, Edith M. “UN: Global population to reach 8.1 billion by 2025”, Last Update: June 13th 2013, http://www.businessweek.com/ap/2013-06-13/un-world-population-to-reach-8-dot-1-billion-in-2025 /ap/2013-06-13/un-world-population-to-reach-8-dot-1-billion-in-2025
Patrick, Stewart M. “The Coming Global Water Crisis”, Last Update: May 9th 2102, http://www.theatlantic.com/international/archive/2012/05/the-coming-global-water-crisis/256896/ /international/archive/2012/05/the-coming-global-water-crisis/256896/
UN Waterb, “Water Use”, http://www.unwater.org/statistics_use.html , 2013.
WHOd, “Global surveillance, prevention and control of chronic respiratory diseases: a comprehensive approach”, http://www.who.int/gard/publications/GARD_Manual/en/index.html /gard/publications/GARD_Manual/en/index.html, 2007.
American Academy of Allergy Asthma & Immunology, “Asthma Statistics”, http://www.aaaai.org/about-the-aaaai/newsroom/asthma-statistics.aspx /about-the-aaaai/newsroom/asthma-statistics.aspx, 2013.
McAdams, Eric, Claudine Gehin, Bertrand Massot, and James McLaughlin, “The Challenges Facing Wearable Sensor Systems,” in 9th International Conference on Wearable Micro and Nano Technologies for Personalized Health, Porto, 2012, pp. 196–202.
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits any noncommercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this chapter or parts of it.
The images or other third party material in this chapter are included in the chapter’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the chapter’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.