Title

Safety Risk Assessment and Warning System at Engineering Laboratory Through IoT Technologies

Publication Name

Lecture Notes in Electrical Engineering

Abstract

Common contributing factors associated to accidents or near-misses in laboratories arises due to risks related to improper use or maintenance of laboratory test equipment and machine. Hence, maintenance and regular inspection of laboratory test equipment and machine are essential parts of safety activity. The project exploits dominance of Internet of Things (IoT) used in many applications to leverage combination of networks and radio frequency identification (RFID) tags technologies to gauge safety risks associated with laboratory inventory in an automated manner. Thus, this paper makes the following contributions:(1) developed an automated inventory laboratory management system that enable test and measurement equipment and machine to be traceable by RFID technology (2) generated an analysis output using informatics as a diagnostic component to improve safety risks presented by test and measurement equipment and machine and (3) developed a graphical user interface that served as the graphical output in monitoring and controlling safety status. Critical issues associated with safety risks which include maintenance schedules, calibration dates, outdated equipment and inventory of equipment are gauged by this system. Subsequently it successfully provides graphical notification on each issue which reflects intact, caution and warning status with green, yellow and red colour codes respectively. In addition, graphical information highlights percentage of progress to stress the severity of the evaluated issue to the technical personnel. This smart system initiates electronic-mail notification to prompt proactive actions to be taken by the technical personnel in a timely manner to mitigate potential accidents or near-misses within the laboratory settings.

Open Access Status

This publication is not available as open access

Volume

741 LNEE

First Page

13

Last Page

23

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Link to publisher version (DOI)

http://dx.doi.org/10.1007/978-981-33-6490-5_2