We present HapSense, a single-volume soft haptic I/O device with uninterrupted dual functionalities of force sensing and vibrotactile actuation. To achieve both input and output functionalities, we employ a ferroelectric electroactive polymer as core functional material with a multilayer structure design. We introduce a haptic I/O hardware that supports tunable high driving voltage waveform for vibrotactile actuation while insitu sensing a change in capacitance from contact force. With mechanically soft nature of fabricated structure, HapSense can be embedded onto various object surfaces including but not limited to furniture, garments, and the human body. Through a series of experiments and evaluations, we characterized physical properties of HapSense and validated the feasibility of using soft haptic I/O with real users. We demonstrated a variety of interaction scenarios using HapSense.

It is projected that, within the coming decade, there will be more than 50 billion smart objects connected to the Internet of Things (IoT). These smart objects, which connect the physical world with the world of computing infrastructure, are expected to pervade all aspects of our daily lives and revolutionize a number of application domains such as healthcare, energy conservation, transportation, etc. In this paper, we present an overview of the challenges involved in designing energy-efficient IoT edge devices and describe recent research that has proposed promising solutions to address these challenges. First, we outline the challenges involved in efficiently supplying power to an IoT device. Next, we discuss the role of emerging memory technologies in making IoT devices energy-efficient. Finally, we discuss the potential impact that approximate computing can have in increasing the energy-efficiency of wearables and other compute-intensive IoT devices.

The lack of post-deployment visibility into system behavior is one of the major challenges in ensuring the reliable operation of implantable medical devices (IMDs). While wireless connectivity is becoming common in IMDs for monitoring device status, conventional wireless links incur significant energy overheads for data acquisition, processing, and active radio transmission. While low-power transceivers have been introduced to reduce the energy consumed by the radio itself, the energy consumed by the microcontroller for processing data and controlling the radio has often been overlooked. As a result, in IMDs that have a stringent energy constraint, prolonged signal monitoring over a wireless channel is infeasible due to this prohibitively high power consumption.

Location is a fundamental service for mobile computing. Typical GPS receivers, although widely available for navigation purposes, may consume too much energy to be useful for many applications. Observing that in many sensing scenarios, the location information can be post-processed when the data is uploaded to a server, we design a cloud-offloaded GPS (CO-GPS) solution that allows a sensing device to aggressively duty-cycle its GPS receiver and log just enough raw GPS signal for post-processing. Leveraging publicly available information such as GNSS satellite ephemeris and an Earth elevation database, a cloud service can derive good quality GPS locations from a few milliseconds of raw data. Using our design of a portable sensing device platform called CLEON, we evaluate the accuracy and efficiency of the solution. Compared to more than 30 seconds of heavy signal processing on standalone GPS receivers, we can achieve three orders of magnitude lower energy consumption per location tagging.

Implantable and wearable medical devices are used for monitoring, diagnosis, and treatment of an ever-increasing range of medical conditions, leading to an improved quality of life for patients. The addition of wireless connectivity to medical devices has enabled post-deployment tuning of therapy and access to device data virtually anytime and anywhere but, at the same time, has led to the emergence of security attacks as a critical concern. While cryptography and secure communication protocols may be used to address most known attacks, the lack of a viable secure connection establishment and key exchange mechanism is a fundamental challenge that needs to be addressed. We propose a vibration-based secure side channel between an external device (medical programmer or smartphone) and a medical device. Vibration is an intrinsically short-range, user-perceptible channel that is suitable for realizing physically secure communication at low energy and size/weight overheads. We identify and address key challenges associated with the vibration channel, and propose a vibration-based wakeup and key exchange scheme, named SecureVibe, that is resistant to battery drain attacks. We analyze the risk of acoustic eavesdropping attacks and propose an acoustic masking countermeasure. We demonstrate and evaluate vibration-based wakeup and key exchange between a smartphone and a prototype medical device in the context of a realistic human body model.

Transiently Powered Computers (TPCs) are a new class of batteryless embedded systems that depend solely on energy harvested from external sources for performing computations. Enabling long-running computations on TPCs is a major challenge due to the highly intermittent nature of the power supply (often bursts of < 100ms), resulting in frequent system reboots. Prior work seeks to address this issue by frequently checkpointing system state in flash memory, preserving it across power cycles. However, this involves a substantial overhead due to the high erase/write times of flash memory. This article proposes the use of Ferroelectric RAM (FRAM), an emerging nonvolatile memory technology that combines the benefits of SRAM and flash, to seamlessly enable long-running computations in TPCs. We propose a lightweight, in-situ checkpointing technique for TPCs using FRAM that consumes only 30 nJ while decreasing the time taken for saving and restoring a checkpoint to only 21.06μ s , which is over two orders of magnitude lower than the corresponding overhead using flash. We have implemented and evaluated our technique, Q uick R ecall , using the TI MSP430FR5739 FRAM-enabled microcontroller. Experimental results show that our highly-efficient checkpointing translate to significant speedup (1.25x - 8.4x) in program execution time and reduction (∼3x) in application-level energy consumption.

Various industry forecasts project that, by 2020, there will be around 50 billion devices connected to the Internet of Things (IoT), helping to engineer new solutions to societal-scale problems such as healthcare, energy conservation, transportation, etc. Most of these devices will be wireless due to the expense, inconvenience, or in some cases, the sheer infeasibility of wiring them. Further, many of them will have stringent size constraints. With no cord for power and limited space for a battery, powering these devices (to achieve several months to possibly years of unattended operation) becomes a daunting challenge. This paper highlights some promising directions for addressing this challenge, focusing on three main building blocks: (a) the design of ultra-low power hardware platforms that integrate computing, sensing, storage, and wireless connectivity in a tiny form factor, (b) the development of intelligent system-level power management techniques, and (c) the use of environmental energy harvesting to make IoT devices self-powered, thus decreasing -- in some cases, even eliminating -- their dependence on batteries. We discuss these building blocks in detail and illustrate case-studies of systems that use them judiciously, including the QUBE wireless embedded platform, which exploits the characteristics of emerging non-volatile memory technologies to seamlessly and efficiently enable long-running computations in systems that experience frequent power loss (i.e., intermittently powered systems).

We demonstrate the CLEO mobile sensing platform, including ultra-portable, low-power sensors, phone-based data upload software, and a location resolution and data management web service in the cloud. The sensing platform leverages cloud-offloaded GPS (CO-GPS) for location sensing. A sensor communicates with mobile devices using an audio-port-based connector. The back-end cloud service supports OData protocol to make data accessible to other systems, such as World-Wide Telescope (WWT).