P. T. V. Bhuvaneswari

Solar Energy Harvesting for Wireless Sensor Networks

The commercially available sensor nodes are battery-driven devices. A number of nodes together constitute a network. As days proceed, the batteries used in the nodes lose their charge and subsequently get isolated from the network. Many energy harvesting schemes have been proposed to alleviate this problem. In this paper, a solar energy based energy harvesting scheme is proposed. This scheme works on the principle of photo-voltaic effect. A recharging circuitry is also designed, that recharges the batteries of the nodes when the charge drops below a threshold level. This leads to strengthening the lifetime of the nodes as well as the network. Compatibility and low power design are the two major salient features of the designed circuitry. The performance of the circuit is also tested with the MICAz hardware.

An Efficient Mobility Based Localization in Underwater Sensor Networks

Underwater Wireless Sensor Network (UWSN) has attracted significant attention recently from both academia and industry, as it provides a promising solution to aquatic environmental monitoring and exploration. Due to the limitation of electromagnetic waves, underwater sensor networks utilize acoustic signals that have high error rate, propagation delay and limited bandwidth for data communication. By adopting predictable mobility patterns of underwater objects, we propose a scheme, called Efficient Mobility Based Localization (EMBL) to determine the location information of sensor node in UWSN. The proposed EMBL scheme is divided into two parts, anchor node localization and ordinary node localization. During the localization process, every node predicts its future mobility pattern according to its past known location information, and estimate its future location. The proposed EMBL scheme is simulated in MATLAB and compared with the existing scheme in terms of localization coverage, localization error, average communication cost. It is found that proposed EMBL scheme outperforms the existing schemes.

Complex Event Processing for object tracking and intrusion detection in Wireless Sensor Networks

Complex Event Processing (CEP) has received wider acceptability due to its systematic and multilevel architecture driven concept approach. CEP is an emerging technology in the field of data processing and identifying patterns of interest from multiple streams of events. High levels of integrated self learning applications can be developed. CEP is used in development of applications which have to deal with voluminous streams of incoming data with the task of finding meaningful events or patterns of events, and respond to the events of interest in real time. In this paper a CEP based application for object detection tracking in a Wireless Sensor Network (WSN) environment is proposed. Also the detection of an intruder using semantic query processing is proposed. ESPER, an open source Complex Event Processing engine is used to develop the application.

Complex Event Processing for Object Tracking in Wireless Sensor Networks

Complex Event Processing (CEP) is a relatively new, but got wider acceptability due to its systematic and multi level architecture driven concept approach. CEP is an emerging technology for processing and identifying patterns of interest from multiple streams of events. CEP is used in development of applications which have to deal with voluminous streams of incoming data with the task of finding meaningful events or patterns of events, and respond to the events of interest in real time. In this paper a CEP based application for object detection and tracking in a Wireless Sensor Network (WSN) environment is proposed. Also the detection of an intruder using semantic query processing is proposed.

Adaptive Traffic Signal Flow Control Using Wireless Sensor Networks

The growth and scale of vehicles today makes management of traffic a constant problem. Measures such as toll based systems with electronic smart card recognition, advance notification on traffic status and fixed time control signaling are some of the measures considered to alleviate the traffic woes of passengers. However a sizeable sum of problems still exists due to incomplete utilization of the road systems. In this paper, an approach to make the traffic signal adaptive to the dynamic traffic flow using wireless sensor network is proposed. The proposed approach is simulated in LabView software and compared with the existing fixed time control scheme. From the results obtained it is observed that the proposed approach outperforms the existing approaches.

Enhanced Call Admission Control for WiMAX networks

Existing Call Admission Control (CAC) mechanism in IEEE 802.16 Broadband Wireless Access (BWA) standard gives priority for VoIP calls in busy hour. The mechanism analyses the performance of UGS service without considering the arrival of non-UGS services. This leads to lack of fairness since the usage of video streaming is also increasing day by day. However the proposed Enhanced Call Admission Control (ECAC) mechanism analyses the performance of non-UGS services with UGS arrival kept constant, thereby ensuring fairness to some extent. The proposed ECAC is simulated in QualNet Version 5.0.2 simulator. From the result, it is found that the proposed mechanism provides the level at which the bandwidth reservation for VoIP calls can be limited.

Distance based transmission power control scheme for indoor wireless sensor network

This paper proposes a Distance Based Transmission Power Control (DBTPC) scheme for selecting Optimal Transmission Power for Indoor Wireless Sensor Network. The proposed work consists of two phases namely Localization phase and data transfer phase. In Localization phase, the relative coordinate of the unknown sensor node with respect to anchor sensor node is estimated by the proposed Received Signal Strength (RSS) based localization algorithm. By performing neighbor discovery process, each node obtains the distance information of its neighboring nodes. Based on this information, in data transfer phase it dynamically controls its transmission power level to reach their neighboring node with acceptable RSS value. This is achieved by the proposed distributed Distance Based Transmission Power Control (DBTPC) scheme. The Optimal Transmission Power (OTP) can be adaptively selected by the proposed DBTPC scheme. This ensures energy efficiency in sensor node and thereby increases the lifetime of the network.

Humanoid robot based physiotherapeutic assistive trainer for elderly health care

Orthopaedic problems have been a constant and nagging hindrance that has been plaguing the elderly community. The treatment for this requires either medication in hospital or at their home comfort by physiotherapists. The dearth of physiotherapists in India has compounded to this problem. Moreover, the media tools, that are employed to teach physiotherapy, have been found to be monotonous and non-interactive with the patients. In pursuit of finding a solution to this problem, a Physiotherapeutic Assistive Trainer (PAT) for elders using a Humanoid Robot, named Nao has been developed. Seamless interaction between Nao and the elderly patient is achieved using the Text-to-Speech module and sensors present in Nao. Further, it replaces human trainer by carefully monitoring the performance of the elders through the camera, equipped in Nao. The array of physiotherapeutic exercises executed by Nao is repeated when the patient make their request by touching Naos tactile sensor. The performance of the limb and neck movement depicting the motion of Nao is analysed using ADAMS software. The reliability of the developed application is validated in a real-time environment. From the results obtained, it is inferred that the Humanoid Robot based Physiotherapeutic Trainer will be the scope of near future.

Optimal transmission power selection under energy constraints for sensor network localization

In a wireless sensor network nodes can be deployed randomly to collect data from an area of interest. So it is mandatory for each node in the network to be aware of its location in the physical world, in order to map the collected information to the base station. Thus, localization becomes an important technique in sensor networks. Further, power conservation is also an important factor as the nodes are operated with limited battery supply. Hence to increase the lifetime of the network, an energy-efficient localization is required. In this paper, a fine-grained paradigm of localizing sensor nodes based on Received Signal Strength (RSS) under controlled power of anchor nodes is proposed. The transmission power control is achieved by Distance Controlled Transmission Power (DCTP) adjustment algorithm where an anchor node closer to an unknown node operates at low transmission power while the one at farther distance operate at high transmission power. Thus based on the distance of the unknown node with anchor node, the transmission power level of anchor is adjusted. This paper also provides analysis of the impact of various transmission power levels on the proposed localization algorithm. Simulation analysis is carried out in Matlab and the results show the performance of the algorithm in terms of localization accuracy and power consumption.

An Analytical Modeling Design to Select an Optimal Forwarding Neighbor in Lossy Wireless Sensor Networks

In this paper, a cross layer protocol named Location Based Energy Efficient Routing (LBEER) is proposed. The proposed LBEER protocol addresses the physical, link and network layer issues by selecting an optimal forwarding neighbor based on Packet Reception Rate (PRR), Packet Velocity (One-hop delay) and Residual energy metrics. An analytical model for optimal forwarding neighbor selection was derived based on the study carried by varying the one-hop distance, nature of environment and transmission power level on PRR, Average End to End delay and Energy consumption parameters. The protocol is simulated in Ns2 for grid topology of 25 nodes. From the simulation results, it is found that optimal neighbor selection based on maximum weighted value of PRR, Packet Velocity, Residual Energy in LBEER outperforms standalone metrics in terms of Packet Delivery Ratio, Normalized Energy Consumption and Optimality in Average End to End delay is achieved.