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Title BOUNDARY DETECTION USING CONTINUOUS OBJECT TRACKING IN IOT ENABLED WIRELESS SENSOR NETWORKS

Author(s) Nagina Ishaq

Abstract Internet of Things (IoT) has attained implausible consideration in today’s era because of their enormous applications in different fields such as environmental perception, military observing, predictive maintenance and industrial applications. IoT approach, provide numerous considerable advantages to various application domains. IoT acquired radiant consideration throughout the ongoing years on account of arise sort of applications that allows tracking and monitoring. The most transcendent applications offer confinement and detection of continuous objects for example wild fire, toxic gas, mud stream, oil spills, wild fire and so forth. Continuous objects are detected to investigate the boundary of hazardous area and alert the staff for safety. Existing studies lacks accurate, energy efficient and delay minimized boundary detection mechanism for continuous objects. In emergency situation detecting accurate boundary of continuous objects has become note worthy challenge, where reducing the delay and minimizing energy consumption are well thought out as first-class citizens. This work proposes a novel mechanism for detecting the accurate boundary of continuous objects in a fog oriented environment using IoT enabled devices to tackle delay related issues and also maximizing energy efficiency. To avoid high latency rate in communication with cloud computing, a grid based scheme is applied for detecting accurate boundary region of continuous objects. To reduce the energy and latency rate our technique requests only grid’s cluster head for making decisions and fog node estimate the diffusing region of object. The propose work implement through simulation in NS-2. Experiment results show that we get better boundary detection while reducing the transmission delay and energy consumption by comparing to state of the art strategies

Type Thesis/Dissertation MS

Faculty Engineering and Computer Science

Department Computer Science

Language English

Publication Date 2022-03-14

Subject Computer Science

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