Emmanuel Kwesi Baah

Work place: Department of Computer Science and Information Technology, Christian Service University College, Kumasi, Ghana



Research Interests: Information-Theoretic Security, Network Security, Computational Learning Theory, Computer systems and computational processes


Emmanuel Kwesi Baah holds a Bachelor’s degree and a Master of Philosophy degree in Computer Science from Kwame Nkrumah University of Science and Technology and is currently a Doctorate candidate in the same field and institution. He is an avid researcher and is currently a Lecturer at Christian Service University College in the Department of Computer Science and Information Technology. His research interests include Deep learning and Network Security

Author Articles
Error Detection and Correction in Wireless Sensor Networks Using Enhanced Reverse Conversion Algorithm in Healthcare Delivery System

By Prince Modey Dominic Asamoah Stephen Opoku Oppong Emmanuel Kwesi Baah

DOI: https://doi.org/10.5815/ijwmt.2022.05.05, Pub. Date: 8 Oct. 2022

Wireless Sensor Network (WSN) is a group of sensors connected within a geographical area to communicate with each other through wireless media. Although WSN is very important in data collection in the world today, error may occur at any stage of data processing and transmission within WSNs due to its architecture. This study presents error detection and correction in WSNs using a proposed ‘pair wise’ Residue Number System (RNS) reverse converter in a health care delivery system. The proposed RNS reverse converter required (10n+3)_FAbit hardware resources for its implementation making it suitable for sensors. The proposed scheme outperformed Weighted Function and Base Extension algorithms and Field Programmable Analog Arrays using Kalman-filter algorithm schemes in terms of its hardware requirements.

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