Abstract

In recent work Wireless Sensor Networks (WSNs) is designed for transportation and environmental monitoring and have develop over numerous generations. Current demand designed for WSNs, e.g., in smart cities, introduces they necessitate designed for sensing systems with the purpose of be able to cooperate among the surrounding environment’s dynamics and objects. So sensing unit in WSN is optimized through low power designed for tremendously long-term deployments. To reduce power consumption in WSN numerous features, such as information compression and online reconfiguration, are integrated to WSN. But still, if the services become high due to the following constraints such as long service time and low maintenance cost, WSNs need adaptive methods to reduce the power consumption, packet loss, and resource. To solve this problem in recent work proposed a Real-time data visualization and investigative through a representational state transfer (RESTful) Application Programming Interface (API). For efficient data transmission to cloud server, SnowFort, an open source WSN, is introduced for monitoring transportation and location. But in this work still the packet loss is not solved because of uncertain problem, to solve this problem in this work Markov Decision Process (MDP) method have been introduced for monitoring transportation to minimize packet loss. In addition, develops a MDP algorithm robust toward decrease data loss and validates it in a simulation setup. Explain the use of MDP designed for the control of sensor nodes in a WSN second-hand for environmental monitoring. The MDP is designed in the direction of collect best possible information regarding the sensor nodes at the same time as guaranteeing an utmost lifetime of with less packet loss. Extend the MDP through improved resistance toward communication packet missing and experimented using Network simulation setup.

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