Network-aware design-space exploration of a power-efficient embedded application

The paper presents the design and multi-parameter optimization of a networked embedded application for the health-care domain. Several hardware, software, and application parameters, such as clock frequency, sensor sampling rate, data packet rate, are tuned at design- and run-time according to application specifications and operating conditions to optimize hardware requirements, packet loss, power consumption. Experimental results show that further power efficiency can be achieved by considering also communication aspects during design space exploratio

Low-energy finite field arithmetic primitives for implementing security in wireless sensor networks

In this paper we propose the use of identity based encryption (IBE) for ensuring a secure wireless sensor network. In this context we have implemented the arithmetic operations required for the most computationally expensive part of IBE, which is the Tate pairing, in 90 nm CMOS and obtained area, timing and energy figures for the designs. Initial results indicate that a hardware implementation of IBE would meet the strict energy constraint of a wireless sensor network nod

Joint Ultra-wideband and Signal Strength-based Through-building Tracking for Tactical Operations

Accurate device free localization (DFL) based on received signal strength (RSS) measurements requires placement of radio transceivers on all sides of the target area. Accuracy degrades dramatically if sensors do not surround the area. However, law enforcement officers sometimes face situations where it is not possible or practical to place sensors on all sides of the target room or building. For example, for an armed subject barricaded in a motel room, police may be able to place sensors in adjacent rooms, but not in front of the room, where the subject would see them. In this paper, we show that using two ultra-wideband (UWB) impulse radios, in addition to multiple RSS sensors, improves the localization accuracy, particularly on the axis where no sensors are placed (which we call the x-axis). We introduce three methods for combining the RSS and UWB data. By using UWB radios together with RSS sensors, it is still possible to localize a person through walls even when the devices are placed only on two sides of the target area. Including the data from the UWB radios can reduce the localization area of uncertainty by more than 60%.Comment: 9 pages, conference submissio

Development of an integrated low-power RF partial discharge detector

This paper presents the results from integrating a low-power partial discharge detector with a wireless sensor node designed for operating as part of an IEEE 802.15.4 sensor network, and applying an on-line classifier capable of classifying partial discharges in real-time. Such a system is of benefit to monitoring engineers as it provides a means to exploit the RF technique using a low-cost device while circumventing the need for any additional cabling associated with new condition monitoring systems. The detector uses a frequency-based technique to differentiate between multiple defects, and has been integrated with a SunSPOT wireless sensor node hosting an agent-based monitoring platform, which includes a data capture agent and rule induction agent trained using experimental data. The results of laboratory system verification are discussed, and the requirements for a fully robust and flexible system are outlined

A sub-mW IoT-endnode for always-on visual monitoring and smart triggering

This work presents a fully-programmable Internet of Things (IoT) visual sensing node that targets sub-mW power consumption in always-on monitoring scenarios. The system features a spatial-contrast $128\mathrm{x}64$ binary pixel imager with focal-plane processing. The sensor, when working at its lowest power mode ($10\mu W$ at 10 fps), provides as output the number of changed pixels. Based on this information, a dedicated camera interface, implemented on a low-power FPGA, wakes up an ultra-low-power parallel processing unit to extract context-aware visual information. We evaluate the smart sensor on three always-on visual triggering application scenarios. Triggering accuracy comparable to RGB image sensors is achieved at nominal lighting conditions, while consuming an average power between $193\mu W$ and $277\mu W$, depending on context activity. The digital sub-system is extremely flexible, thanks to a fully-programmable digital signal processing engine, but still achieves 19x lower power consumption compared to MCU-based cameras with significantly lower on-board computing capabilities.Comment: 11 pages, 9 figures, submitteted to IEEE IoT Journa

Low-power digital processor for wireless sensor networks

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2005.Includes bibliographical references (p. 69-72).In order to make sensor networks cost-effective and practical, the electronic components of a wireless sensor node need to run for months to years on the same battery. This thesis explores the design of a low-power digital processor for these sensor nodes, employing techniques such as hardwired algorithms, lowered supply voltages, clock gating and subsystem shutdown. Prototypes were built on both a FPGA and ASIC platform, in order to verify functionality and characterize power consumption. The resulting 0.18[micro]m silicon fabricated in National Semiconductor Corporation's process was operational for supply voltages ranging from 0.5V to 1.8V. At the lowest operating voltage of 0.5V and a frequency of 100KHz, the chip performs 8 full-accuracy FFT computations per second and draws 1.2nJ of total energy per cycle. Although this energy/cycle metric does not surpass existing low-energy processors demonstrated in literature or commercial products, several low-power techniques are suggested that could drastically improve the energy metrics of a future implementation.by Daniel Frederic Finchelstein.S.M