Performance analysis of error detection and correction code for wireless sensor networks

Recent advances in wireless communications and electronics have enabled the development of low-cost, low-power, self-organizational, multifunctional wireless sensor networks. Wireless sensor networks can be applied to a wide range of application areas including heath, military and homeland security, environment, industry and commercial, and home. A typical wireless sensor network consists of one or more sink nodes and a large number of sensor nodes scattered in a sensor field. Each of these sensor nodes is capable to collect the data and relay the data back to the sink through a multi-hop architecture. The key challenge in sensor networks is to overcome the energy constraint since each sensor node has limited power. Hence, it is important to minimize the energy used to transmit packets over wireless links; The data transmitted from the sensor nodes are vulnerable to be corrupted by errors induced by noisy channels and other factors. Hence it is necessary to provide a proper error control scheme to reduce the bit error rate (BER) to a desired level without sacrificing other performance. Energy required for error control code has a direct impact on battery power consumption. Since high error rates are inevitable in the wireless environment, energy efficient error detection and correction scheme is vital in wireless sensor networks. However, in the literature, limited work has been focused on the study of energy efficient error control scheme; This thesis is focused on energy-efficient error detection and correction schemes for wireless sensor networks. (Abstract shortened by UMI.)

Comparative Investigation for Energy Consumption of Different Chipsets Based on Scheduling for Wireless Sensor Networks

Rapid progress in microelectromechanical system (MEMS) and radio frequency (RF) design has enabled the development of low-power, inexpensive, and network-enabled microsensors. These sensor nodes are capable of capturing various physical information, such as temperature, pressure, motion of an object, etc as well as mapping such physical characteristics of the environment to quantitative measurements. A typical wireless sensor network (WSN) consists of hundreds to thousands of such sensor nodes linked by a wireless medium. In this paper, we present a comparative investigation of energy consumption for few commercially available chipsets such as TR1001, CC1000 and CC1010 based on different scheduling methods for two types of deployment strategies. We conducted our experiment within the OMNeT++ simulator.Comment: 17 pages, Based on scheduling for Wireless Sensor Network

Relay based thermal aware and mobility support routing protocol for wireless body sensor networks

The evolvement of wireless technologies has enabled revolutionizing the health-care industry by monitor patient health condition requiring early diagnosis and interfering when a chronic situation is taking place. In this regard, miniaturized biosensors have been manufactured to cover various medical applications forming therefore a Wireless Body Sensor Network (WBSN). A WBSN is comprised of several small and low power devices capable of sensing vital signs such as heart rate, blood glucose, body temperature etc.. Although WBSN main purpose is to provide the most convenient wireless setting for the networking of human body sensors, there are still a great number of technical challenges to resolve such as: power source miniaturization, low power transceivers, biocompatibility, secure data transfer, minimum transmission delay and high quality of service. These challenges have to be taken into consideration when creating a new routing protocol for WBSNs. This paper proposes a new Relay based Thermal aware and Mobile Routing Protocol (RTM-RP) for Wireless Body Sensor Networks tackling the problem of high energy consumption and high temperature increase where the mobility is a crucial constraint to handle

Probabilistic approaches to the design of wireless ad hoc and sensor networks

The emerging wireless technologies has made ubiquitous wireless access a reality and enabled wireless systems to support a large variety of applications. Since the wireless self-configuring networks do not require infrastructure and promise greater flexibility and better coverage, wireless ad hoc and sensor networks have been under intensive research. It is believed that wireless ad hoc and sensor networks can become as important as the Internet. Just as the Internet allows access to digital information anywhere, ad hoc and sensor networks will provide remote interaction with the physical world. Dynamics of the object distribution is one of the most important features of the wireless ad hoc and sensor networks. This dissertation deals with several interesting estimation and optimization problems on the dynamical features of ad hoc and sensor networks. Many demands in application, such as reliability, power efficiency and sensor deployment, of wireless ad hoc and sensor network can be improved by mobility estimation and/or prediction. In this dissertation, we study several random mobility models, present a mobility prediction methodology, which relies on the analysis of the moving patterns of the mobile objects. Through estimating the future movement of objects and analyzing the tradeoff between the estimation cost and the quality of reliability, the optimization of tracking interval for sensor networks is presented. Based on the observation on the location and movement of objects, an optimal sensor placement algorithm is proposed by adaptively learn the dynamical object distribution. Moreover, dynamical boundary of mass objects monitored in a sensor network can be estimated based on the unsupervised learning of the distribution density of objects. In order to provide an accurate estimation of mobile objects, we first study several popular mobility models. Based on these models, we present some mobility prediction algorithms accordingly, which are capable of predicting the moving trajectory of objects in the future. In wireless self-configuring networks, an accurate estimation algorithm allows for improving the link reliability, power efficiency, reducing the traffic delay and optimizing the sensor deployment. The effects of estimation accuracy on the reliability and the power consumption have been studied and analyzed. A new methodology is proposed to optimize the reliability and power efficiency by balancing the trade-off between the quality of performance and estimation cost. By estimating and predicting the mass objects\u27 location and movement, the proposed sensor placement algorithm demonstrates a siguificant improvement on the detection of mass objects with nearmaximal detection accuracy. Quantitative analysis on the effects of mobility estimation and prediction on the accuracy of detection by sensor networks can be conducted with recursive EM algorithms. The future work includes the deployment of the proposed concepts and algorithms into real-world ad hoc and sensor networks

Early forest fire detection by vision-enabled wireless sensor networks

Wireless sensor networks constitute a powerful technology particularly suitable for environmental monitoring. With regard to wildfires, they enable low-cost fine-grained surveillance of hazardous locations like wildland-urban interfaces. This paper presents work developed during the last 4 years targeting a vision-enabled wireless sensor network node for the reliable, early on-site detection of forest fires. The tasks carried out ranged from devising a robust vision algorithm for smoke detection to the design and physical implementation of a power-efficient smart imager tailored to the characteristics of such an algorithm. By integrating this smart imager with a commercial wireless platform, we endowed the resulting system with vision capabilities and radio communication. Numerous tests were arranged in different natural scenarios in order to progressively tune all the parameters involved in the autonomous operation of this prototype node. The last test carried out, involving the prescribed burning of a 95 x 20-m shrub plot, confirmed the high degree of reliability of our approach in terms of both successful early detection and a very low false-alarm rate. Journal compilationMinisterio de Ciencia e Innovación TEC2009-11812, IPT-2011-1625-430000Office of Naval Research (USA) N000141110312Centro para el Desarrollo Tecnológico e Industrial IPC-2011100

A multi-sensor based online tool condition monitoring system for milling process

Tool condition monitoring has been considered as one of the key enabling technologies for manufacturing optimization. Due to the high cost and limited system openness, the relevant developed systems have not been widely adopted by industries, especially Small and Medium-sized Enterprises. In this research, a cost-effective, wireless communication enabled, multi-sensor based tool condition monitoring system has been developed. Various sensor data, such as vibration, cutting force and power data, as well as actual machining parameters, have been collected to support efficient tool condition monitoring and life estimation. The effectiveness of the developed system has been validated via machining cases. The system can be extended to wide manufacturing applications

Using wearable sensors for remote healthcare monitoring system

Recent technological advances in wireless communications and wireless sensor networks have enabled the design of low-cost, intelligent, tiny, and lightweight medical sensor nodes that can be strategically placed on human body, create a wireless body area network (WBAN) to monitor various physiological vital signs for a long period of time and providing real-time feedback to the user and medical staff. WBANs promise to re-volutionize health monitoring. In this paper, medical sensors were used to collect physiological data from patients and transmit it to Intelligent Personal digital Assistant (IPDA) using ZigBee/IEEE802.15.4 standard and to medical server using 3G communications. We introduced priority scheduling and data compression into the system to increase transmission rate of physiological critical signals which improve the bandwidth utilization. It also extends the life time of hand-held personal server by reducing power consumption during transmission

Miniature, all-solid-state ion-selective sensor as a detector in autonomous, deployable sensing device

Lowering of the detection limit of ion-selective electrodes (ISEs) as well as their simple construction, low production cost and low power requirements make ISEs an ideal candidate for detector systems that can be integrated into autonomous, deployable sensing devices. Routine analysis and early warning systems are applications that first spring to mind, however great added value can be obtained by integration of many such devices into a wireless sensing network. In this work we describe our work towards the miniaturization of ISEs and their integration of with all-solid-state reference electrode into an all-solid-state sensor with a view of integration in autonomous, deployable sensing device. This work has two avenues: 1) development of a platform that can house all-solid-state ISEs and reference electrodes and 2) development of electronic circuitry for data acquisition and wireless transmission of the data. The latter utilizes novel, in-house made motes (a node in a wireless sensor network that is capable of performing some processing, gathering sensory information and communicating with other connected nodes in the network) that operate at lower frequency and therefore consume lower power then other, commercially available ones. In addition, they are easier to program which bridges the gap of communication between chemists and computer scientists. Intensification of the work in producing all-solid-state reference electrodes has enabled us to work on development of a platform that houses all-solid-state ISEs and reference electrode. We will here describe our progress in this avenue of our research