DEVELOPMENT OF A HYBRID HUMAN RESOURCES LOCATION MONITORING SYSTEM

Abstract

Globalization, evolution of computer technology and the fast pace of technological advancements have affected every facet of human lives and endeavours. Several research works have shown the centrality and importance of Human Resources (HR) to the success and competitive advantage of any organization, hence the need to ensure the monitoring of activities and safety of this all-important factor of production. HR monitoring has evolved over the years from the traditional methods of attendance register and movement books to real time monitoring using several technologies and techniques. The major challenge has been the inability of a single technique to adequately monitor and provide accurate positioning data due to the changing environments of the workplace. This research developed a real-time system for positioning and monitoring of HR using a hybrid Global Positioning System (GPS), Radio Frequency Identification (RFID), cameras and sensors. GPS was used for monitoring and localization in the outdoor environment, RFID was for indoor environment monitoring, cameras were to give visual images of tracked objects while sensors were used for GPS and RFID signals denied areas. Data transmission from tracking devices to the database server was carried out using Long Term Evolution (LTE) network. The research presented an integration of different positioning technologies for the purpose of monitoring the activities of HR and ensuring their availability and safety in the workplace. The proposed model was implemented using Python programming language as frontend and MySQL database management system as backend in a Windows 10 operating system environment. Case study of the monitoring of selected staff of Information and Communication Technology Application Centre (ICTAC) of Adekunle Ajasin University, Akungba-Akoko was used to test the adequacy and practical functions of the model. Results obtained showed that the research produced a higher level of accuracy both in indoor and outdoor environments when compared with similar exiting system. The cost of deployment was also lower than other existing systems because of the use of free and open source software for its development. The system is scalable and very robust and with the use of passive RFID and Arduino microcontroller, power consumption was low.