Field Worker’s Routine Behaviour for Efficient Time Utilization
Munish Mehta1, Rahul Sharma2, Pawan Suthar3
1Munish Mehta, Department of Computer Application, National Institute of Technology, Kurukshetra, India.
2Rahul Sharma, Department of Computer Application, National Institute of Technology, Kurukshetra, India.
3Pawan Suthar, Jodhpur Discom, Department of Electricity, Government of Rajasthan, Bikaner, India.
Manuscript received on 09 August 2019 | Revised Manuscript received on 17 August 2019 | Manuscript Published on 26 August 2019 | PP: 116-120 | Volume-8 Issue-9S August 2019 | Retrieval Number: I10180789S19/19©BEIESP DOI: 10.35940/ijitee.I1018.0789S19
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open-access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: In this paper, we are proposing a monitoring technique that can predict the appropriate time to meet the field officer with more accuracy as compared to general human prediction. To get the routine behaviour of an individual we will keep a track of his online presence on WhatsApp by the “Active Now” status shown beneath the user’s name in the profile. This will help the Personal assistants, secretaries and receptionists to provide right appointment schedule to clients or to those who want to meet a field officer. This all will be done by scraping data from WhatsApp web portal using python modules, storing the judging parameters like unique identification number, date and time stamp, duration of continuous presence and number of sessions in a day, afterwards analyzing the dataset and providing an appropriate routine behaviour prediction. For the sake of efficient utilization of time and resources.
Keywords: Human Behaviour Analysis, Naïve Bayes, Time Utilization, Web Scraping.
Scope of the Article: Cloud Resources Utilization in IoT