VLSI implementation of an energy-aware wake-up detector for an acoustic surveillance sensor network

We present a low-power VLSI wake-up detector for a sensor network that uses acoustic signals to localize ground-base vehicles. The detection criterion is the degree of low-frequency periodicity in the acoustic signal, and the periodicity is computed from the "bumpiness" of the autocorrelation of a one-bit version of the signal. We then describe a CMOS ASIC that implements the periodicity estimation algorithm. The ASIC is functional and its core consumes 835 nanowatts. It was integrated into an acoustic enclosure and deployed in field tests with synthesized sounds and ground-based vehicles.Fil: Goldberg, David H.. Johns Hopkins University; Estados UnidosFil: Andreou, Andreas. Johns Hopkins University; Estados UnidosFil: Julian, Pedro Marcelo. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional del Sur. Departamento de Ingeniería Eléctrica y de Computadoras; ArgentinaFil: Pouliquen, Philippe O.. Johns Hopkins University; Estados UnidosFil: Riddle, Laurence. Signal Systems Corporation; Estados UnidosFil: Rosasco, Rich. Signal Systems Corporation; Estados Unido

Selecting source image sensor nodes based on 2-hop information to improve image transmissions to mobile robot sinks in search \& rescue operations

We consider Robot-assisted Search $\&$ Rescue operations enhanced with some fixed image sensor nodes capable of capturing and sending visual information to a robot sink. In order to increase the performance of image transfer from image sensor nodes to the robot sinks we propose a 2-hop neighborhood information-based cover set selection to determine the most relevant image sensor nodes to activate. Then, in order to be consistent with our proposed approach, a multi-path extension of Greedy Perimeter Stateless Routing (called T-GPSR) wherein routing decisions are also based on 2-hop neighborhood information is proposed. Simulation results show that our proposal reduces packet losses, enabling fast packet delivery and higher visual quality of received images at the robot sink

An Energy Efficient Self-healing Mechanism for Long Life Wireless Sensor Networks

In this paper, we provide an energy efficient self- healing mechanism for Wireless Sensor Networks. The proposed solution is based on our probabilistic sentinel scheme. To reduce energy consumption while maintaining good connectivity between sentinel nodes, we compose our solution on two main concepts, node adaptation and link adaptation. The first algorithm uses node adaptation technique and permits to distributively schedule nodes activities and select a minimum subset of active nodes (sentry) to monitor the interest region. And secondly, we in- troduce a link control algorithm to ensure better connectiv- ity between sentinel nodes while avoiding outliers appearance. Without increasing control messages overhead, performances evaluations show that our solution is scalable with a steady energy consumption. Simulations carried out also show that the proposed mechanism ensures good connectivity between sentry nodes while considerably reducing the total energy spent.Comment: 6 pages, 8 figures. arXiv admin note: text overlap with arXiv:1309.600

Energy Efficient Approach for Surveillance Applications Based on Self Organized Wireless Sensor Networks

AbstractSurveillance applications based on Wireless Sensor Networks (WSNs) are energy consumption sensitive. Such applications require low energy consumption in order to extend network lifetime. In this paper, we are interested in event detection around strategic sites (e.g., oil or military sites). We propose energy efficient approach which consists of identifying and using network boundary nodes as sentries, i.e., they are always in active mode and are responsible of detecting events, sending and relaying alert messages to the sink. Remaining nodes are used as relay nodes only. They alternate between active and sleep modes in order to reduce energy consumption. Simulation results show that our approach increases significantly network lifetime and provides an acceptable percentage of alerts delivered to the sink

An improved energy efficient approach for wsn based tracking applications

Tracking systems using a high number of low cost sensor nodes have been proposed for use in diverse applications including civil, military, and wildlife monitoring applications. In tracking applications, each sensor node attempts to send the target's location information to a sink node. Deploying a tracking system with a high number of sensor nodes results in the following limitations: high packet dropping rate, high congestion, transmission delay, and high power-consumption. Data aggregation schemes can reduce the number of messages transmitted over the network, while prediction schemes can decrease the number of activated beacon nodes in the tracking process. Consequently, data aggregation and prediction approaches can reduce the energy consumed during the tracking process. In this paper, we propose and implement an energy efficient approach for WSN-based tracking applications by integrating both a novel data aggregation method with a simple prediction approach. Three metrics are utilized for the evaluation purposes: total number of messages transmitted in the network, overall power-consumption, and the quality of the tracking accuracy. The proposed system is simulated using the NS2 simulation environment

Use of wireless sensors to improve robot lifetime for multi-threat containment

Autonomous robots can be used in a decentralized environment to contain threats. While working in this capacity, these motor propelled robots are constantly moving, therefore drawing a large amount of current from the battery. If these algorithms are to be implemented in hardware, it is important to ensure that the robots move only when necessary in an effort to optimize battery life. This work introduces static wireless sensors to assist robots in detecting threats. By having a sufficient number of wireless sensors available to detect threats, it is hypothesized that a similar containment performance can be achieved with less robot movements. When not actively containing threats, the robots may enter a sleep mode thus optimizing energy conservation. The notion of multimode operations has been utilized in other wireless sensor network applications. In the field of cooperative robotics, however, little has been investigated for system performance when both mobile robots and static sensors coexist. This work leverages previously developed multi-threat containment algorithms and the notion of multi-mode operations from wireless sensor network research community and examines the scenarios where wireless sensors can benefit the overall system performance. Battery models and additional sensor and obstacle objects are introduced to a previously developed simulator, MAHESHDAS. Various battery models and parameters are considered to mimic a realistic environment. The sensor nodes occupy a small amount of physical space and therefore assist the robots while also limiting their movements. Robots are assumed to be ground vehicles, and will need to avoid collisions of each other as well as sensor nodes and other obstacles. Repulsion forces are used to model the collision avoidance between the various objects. The percentage of threats contained, the time to contain threats, and the average robot lifetime are compared in different operational scenarios. The simulation results demonstrate that the introduction of wireless sensors improve the average robot lifetime when the threats do not occur too often and when the sensor repulsion force is relatively small. Uniform sensor placement is also shown to perform better than random deployment

Solar energy harvesting and software enhancements for autonomous wireless smart sensor networks

Civil infrastructure is the backbone of modern society, and maintaining said infrastructure is critical in maintaining healthy society. Wireless smart sensors (WSSs) provide a means to effectively monitor the performance of buildings and bridges to improve maintenance practices, minimize the costs of repair, and improve public safety through a process called structural health monitoring (SHM). WSSs, traditionally powered by batteries, are limited in the length of time they can operate autonomously. The frequent need to change batteries in the networks can drive up maintenance costs and diminish the advantage first realized with WSSs. Efforts have been made to minimize the power consumption of WSSs operating in SHM networks, but there have been a limited number of new power supply options, such as energy harvesting, used in full-scale SHM applications. This research develops a solar energy harvesting system to provide power to Imote2 WSS platform and increase the long-term autonomy of wireless smart sensor networks (WSSNs). The approach is validated on a cable stayed bridge in South Korea. Additionally, software enhancements are introduced to allow sensor data to be stored in non-volatile memory, potentially further enhancing the efficacy of WSSNs. This research has resulted in greater overall autonomy of WSSNs

Power management techniques in an FPGA-Based WSN node for high performance application

In this work, the power management techniques implemented in a high-performance node for Wireless Sensor Networks (WSN) based on a RAM-based FPGA are presented. This new node custom architecture is intended for high-end WSN applications that include complex sensor management like video cameras, high compute demanding tasks such as image encoding or robust encryption, and/or higher data bandwidth needs. In the case of these complex processing tasks, yet maintaining low power design requirements, it can be shown that the combination of different techniques such as extensive HW algorithm mapping, smart management of power islands to selectively switch on and off components, smart and low-energy partial reconfiguration, an adequate set of save energy modes and wake up options, all combined, may yield energy results that may compete and improve energy usage of typical low power microcontrollers used in many WSN node architectures. Actually, results show that higher complexity tasks are in favor of HW based platforms, while the flexibility achieved by dynamic and partial reconfiguration techniques could be comparable to SW based solutions