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A Fuzzy Approach for an IoT-based Automated Employee Performance Appraisal

Jaideep Kaur1, Kamaljit Kaur2

Guru Nanak Dev University, Amritsar, Punjab India.
Guru Nanak Dev University, Amritsar, Punjab India

Computers, Materials & Continua 2017, 53(1), 23-36. https://doi.org/10.3970/cmc.2017.053.024

Abstract

The ubiquitous Internet of Things (IoT) through RFIDs, GPS, NFC and other wireless devices is capable of sensing the activities being carried around Industrial environment so as to automate industrial processes. In almost every industry, employee performance appraisal is done manually which may lead to favoritisms. This paper proposes a framework to perform automatic employee performance appraisal based on data sensed from IoT. The framework classifies raw IoT data into three activities (Positive, Negative, Neutral), co-locates employee and activity in order to calculate employee implication and then performs cognitive decision making using fuzzy logic. From the experiments carried out it is observed that automatic system has improved performance of employees. Also the impact of the proposed system leads to motivation among employees. The simulation results show how fuzzy approach can be exploited to reward or penalize employees based on their performance.

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Cite This Article

APA Style
Kaur, J., Kaur, K. (2017). A fuzzy approach for an iot-based automated employee performance appraisal. Computers, Materials & Continua, 53(1), 23-36. https://doi.org/10.3970/cmc.2017.053.024
Vancouver Style
Kaur J, Kaur K. A fuzzy approach for an iot-based automated employee performance appraisal. Comput Mater Contin. 2017;53(1):23-36 https://doi.org/10.3970/cmc.2017.053.024
IEEE Style
J. Kaur and K. Kaur, “A Fuzzy Approach for an IoT-based Automated Employee Performance Appraisal,” Comput. Mater. Contin., vol. 53, no. 1, pp. 23-36, 2017. https://doi.org/10.3970/cmc.2017.053.024



cc Copyright © 2017 The Author(s). Published by Tech Science Press.
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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