Artificial Neural Network Application for Error Estimation in Wireless Sensor Network
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Date
2017-05-06
Journal Title
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Publisher
IEEE Forum (ICSTEM)
Abstract
This paper comes up with an error estimation model for Wireless Sensor Nodes,, the integrity of data received after transmission within a signal coverage range less or equal to 45 metres is analysed, Neural Network linear regression method was used to evolve resolve equation that compares error with weight of data received as δ℮(w) against δwij , an equation for error rate was also evolved after carefully comparing between data packet transmitted and Packet received, error rate er for sensor node was calculated to be 0.00918 thereby establishing the fact that expected packet to be received for every data transmitted is the product of er and Packet Transmitted.
Description
This paper presents an error estimation model for wireless sensor nodes by analyzing the integrity of data received within a transmission range of up to 45 meters. Using a neural network linear regression approach, the study derives a relationship between transmission error and data weight, represented as δ℮(w) against δwij. Additionally, an error rate equation is formulated by comparing transmitted and received data packets. The calculated error rate (er) for the sensor node is 0.00918, indicating that the expected number of packets successfully received is directly proportional to the product of the error rate and the number of packets transmitted. This model provides a quantitative basis for assessing data reliability in wireless sensor networks.
Keywords
Packet, Data, Neural Network, Wireless Sensor Network
Citation
Agajo, J., Kolo, J. G., Maliki, D., Umar, B. U., Inalegwu, O. C., (2017). Artificial Neural Network Application for Error Estimation in Wireless Sensor Network. ISER-173rd International Conference of Science, Technology, Engineering and Management (ICSTEM) Dubai, UAE. Pp 22-26.