Gesture Based Home Automation for the Physically Disabled

Paralysis and motor-impairments can greatly reduce the autonomy and quality of life of a patient while presenting a major recurring cost in home-healthcare. Augmented with a non-invasive wearable sensor system and home-automation equipment, the patient can regain a level of autonomy at a fraction of the cost of home nurses. A system which utilizes sensor fusion, low-power digital components, and smartphone cellular capabilities can extend the usefulness of such a system to allow greater adaptivity for patients with various needs. This thesis develops such a system as a Bluetooth enabled glove device which communicates with a remote web server to control smart-devices within the home. The power consumption of the system is considered as a major component to allow the system to operate while requiring little maintenance, allowing for greater patient autonomy. The system is evaluated in terms of power consumption and accuracy to prove its viability as a home accessibility tool

Movers and Shakers: Kinetic Energy Harvesting for the Internet of Things

Numerous energy harvesting wireless devices that will serve as building blocks for the Internet of Things (IoT) are currently under development. However, there is still only limited understanding of the properties of various energy sources and their impact on energy harvesting adaptive algorithms. Hence, we focus on characterizing the kinetic (motion) energy that can be harvested by a wireless node with an IoT form factor and on developing energy allocation algorithms for such nodes. In this paper, we describe methods for estimating harvested energy from acceleration traces. To characterize the energy availability associated with specific human activities (e.g., relaxing, walking, cycling), we analyze a motion dataset with over 40 participants. Based on acceleration measurements that we collected for over 200 hours, we study energy generation processes associated with day-long human routines. We also briefly summarize our experiments with moving objects. We develop energy allocation algorithms that take into account practical IoT node design considerations, and evaluate the algorithms using the collected measurements. Our observations provide insights into the design of motion energy harvesters, IoT nodes, and energy harvesting adaptive algorithms.Comment: 15 pages, 11 figure

Energy harvesting and wireless transfer in sensor network applications: Concepts and experiences

Advances in micro-electronics and miniaturized mechanical systems are redefining the scope and extent of the energy constraints found in battery-operated wireless sensor networks (WSNs). On one hand, ambient energy harvesting may prolong the systems lifetime or possibly enable perpetual operation. On the other hand, wireless energy transfer allows systems to decouple the energy sources from the sensing locations, enabling deployments previously unfeasible. As a result of applying these technologies to WSNs, the assumption of a finite energy budget is replaced with that of potentially infinite, yet intermittent, energy supply, profoundly impacting the design, implementation, and operation of WSNs. This article discusses these aspects by surveying paradigmatic examples of existing solutions in both fields and by reporting on real-world experiences found in the literature. The discussion is instrumental in providing a foundation for selecting the most appropriate energy harvesting or wireless transfer technology based on the application at hand. We conclude by outlining research directions originating from the fundamental change of perspective that energy harvesting and wireless transfer bring about

Systems for pervasive electronics and interfaces

Energy Harvesting Active Networked Tags (EnHANTs) are a new type of wireless device in the domain between RFIDs and sensor networks. Future EnHANTs will be small, flexible, and self-powered devices that can be attached to everyday objects that are traditionally not networked to enable "Internet of Things" applications. This work describes the design and development of the EnHANT prototypes and testbed. The current prototypes use thin-film photovoltaics optimized for indoor light harvesting, form multihop networks using ultra-low-power Ultra-Wideband Impulse Radio (UWB-IR) transceivers, and implement energy harvesting adaptive networking protocols. The current testbed enables the evaluation of different algorithms by exposing individual prototypes to repeatable light conditions based on real-world irradiance data. New approaches to characterizing the energy available to energy harvesting devices were explored. A mobile data-logger was used to record the intensity of ambient light, determine the light source, and record the acceleration from motion during different real world activities. These traces were used to model the behavior of photovoltaic and inertial energy harvesters in real world deployments and can be replayed in the EnHANTs testbed. In addition, new techniques to evaluate the efficiency of different photovoltaic technologies under indoor illumination were developed. A proof-of-concept system was built to characterize photovoltaics under a standardized set of conditions in which the radiant intensity and spectral composition of the light source were systematically varied. Techniques to structure student research projects within the EnHANTs project were developed. Project-based learning approaches were implemented to engage students using real-world system development constraints. A survey of the students showed that this approach is an effective method for developing technical, professional, and soft skills. Open source hardware was also applied to EnHANTs project and extended into other domains. A laboratory-based class in flat panel display technology was developed. The course introduces fundamental concepts of display systems and reinforces these concepts through the fabrication of three display devices. A lab kit platform was developed to enable remote students to use low-cost, course specific hardware to complete the lab exercises remotely. This platform was also applied to external projects targeted at non-university students. A workshop was developed to teach artists, designers, and hobbyists how to design and build custom user interfaces using thin-film electronics and rapid prototyping tools. Surveys of the students and workshop participants showed that this platform is an effective teaching tool and can be easily adapted and expanded

Transiently Powered Computers

Demand for compact, easily deployable, energy-efficient computers has driven the development of general-purpose transiently powered computers (TPCs) that lack both batteries and wired power, operating exclusively on energy harvested from their surroundings. TPCs\u27 dependence solely on transient, harvested power offers several important design-time benefits. For example, omitting batteries saves board space and weight while obviating the need to make devices physically accessible for maintenance. However, transient power may provide an unpredictable supply of energy that makes operation difficult. A predictable energy supply is a key abstraction underlying most electronic designs. TPCs discard this abstraction in favor of opportunistic computation that takes advantage of available resources. A crucial question is how should a software-controlled computing device operate if it depends completely on external entities for power and other resources? The question poses challenges for computation, communication, storage, and other aspects of TPC design. The main idea of this work is that software techniques can make energy harvesting a practicable form of power supply for electronic devices. Its overarching goal is to facilitate the design and operation of usable TPCs. This thesis poses a set of challenges that are fundamental to TPCs, then pairs these challenges with approaches that use software techniques to address them. To address the challenge of computing steadily on harvested power, it describes Mementos, an energy-aware state-checkpointing system for TPCs. To address the dependence of opportunistic RF-harvesting TPCs on potentially untrustworthy RFID readers, it describes CCCP, a protocol and system for safely outsourcing data storage to RFID readers that may attempt to tamper with data. Additionally, it describes a simulator that facilitates experimentation with the TPC model, and a prototype computational RFID that implements the TPC model. To show that TPCs can improve existing electronic devices, this thesis describes applications of TPCs to implantable medical devices (IMDs), a challenging design space in which some battery-constrained devices completely lack protection against radio-based attacks. TPCs can provide security and privacy benefits to IMDs by, for instance, cryptographically authenticating other devices that want to communicate with the IMD before allowing the IMD to use any of its battery power. This thesis describes a simplified IMD that lacks its own radio, saving precious battery energy and therefore size. The simplified IMD instead depends on an RFID-scale TPC for all of its communication functions. TPCs are a natural area of exploration for future electronic design, given the parallel trends of energy harvesting and miniaturization. This work aims to establish and evaluate basic principles by which TPCs can operate

Sophisticated Batteryless Sensing

Wireless embedded sensing systems have revolutionized scientific, industrial, and consumer applications. Sensors have become a fixture in our daily lives, as well as the scientific and industrial communities by allowing continuous monitoring of people, wildlife, plants, buildings, roads and highways, pipelines, and countless other objects. Recently a new vision for sensing has emerged---known as the Internet-of-Things (IoT)---where trillions of devices invisibly sense, coordinate, and communicate to support our life and well being. However, the sheer scale of the IoT has presented serious problems for current sensing technologies---mainly, the unsustainable maintenance, ecological, and economic costs of recycling or disposing of trillions of batteries. This energy storage bottleneck has prevented massive deployments of tiny sensing devices at the edge of the IoT. This dissertation explores an alternative---leave the batteries behind, and harvest the energy required for sensing tasks from the environment the device is embedded in. These sensors can be made cheaper, smaller, and will last decades longer than their battery powered counterparts, making them a perfect fit for the requirements of the IoT. These sensors can be deployed where battery powered sensors cannot---embedded in concrete, shot into space, or even implanted in animals and people. However, these batteryless sensors may lose power at any point, with no warning, for unpredictable lengths of time. Programming, profiling, debugging, and building applications with these devices pose significant challenges. First, batteryless devices operate in unpredictable environments, where voltages vary and power failures can occur at any time---often devices are in failure for hours. Second, a device\u27s behavior effects the amount of energy they can harvest---meaning small changes in tasks can drastically change harvester efficiency. Third, the programming interfaces of batteryless devices are ill-defined and non- intuitive; most developers have trouble anticipating the problems inherent with an intermittent power supply. Finally, the lack of community, and a standard usable hardware platform have reduced the resources and prototyping ability of the developer. In this dissertation we present solutions to these challenges in the form of a tool for repeatable and realistic experimentation called Ekho, a reconfigurable hardware platform named Flicker, and a language and runtime for timely execution of intermittent programs called Mayfly

Low-Power and Programmable Analog Circuitry for Wireless Sensors

Embedding networks of secure, wirelessly-connected sensors and actuators will help us to conscientiously manage our local and extended environments. One major challenge for this vision is to create networks of wireless sensor devices that provide maximal knowledge of their environment while using only the energy that is available within that environment. In this work, it is argued that the energy constraints in wireless sensor design are best addressed by incorporating analog signal processors. The low power-consumption of an analog signal processor allows persistent monitoring of multiple sensors while the device\u27s analog-to-digital converter, microcontroller, and transceiver are all in sleep mode. This dissertation describes the development of analog signal processing integrated circuits for wireless sensor networks. Specific technology problems that are addressed include reconfigurable processing architectures for low-power sensing applications, as well as the development of reprogrammable biasing for analog circuits

Low-Power and Programmable Analog Circuitry for Wireless Sensors

Embedding networks of secure, wirelessly-connected sensors and actuators will help us to conscientiously manage our local and extended environments. One major challenge for this vision is to create networks of wireless sensor devices that provide maximal knowledge of their environment while using only the energy that is available within that environment. In this work, it is argued that the energy constraints in wireless sensor design are best addressed by incorporating analog signal processors. The low power-consumption of an analog signal processor allows persistent monitoring of multiple sensors while the device\u27s analog-to-digital converter, microcontroller, and transceiver are all in sleep mode. This dissertation describes the development of analog signal processing integrated circuits for wireless sensor networks. Specific technology problems that are addressed include reconfigurable processing architectures for low-power sensing applications, as well as the development of reprogrammable biasing for analog circuits