A gas monitoring system plays an important role in almost all the chemical and process industries as it prevents accidents. Many of the existing gas monitoring systems employ distributive sensing, an expensive and a complex process. The system discussed in this paper presents an alternative approach which consists of a mobile robot capable of moving on its own with obstacle avoidance algorithm. It can quickly scan hazardous gasses, smoke, fire etc. in all the parts of an industrial complex and can immediately generate an alarm and send SMS to all the concerned people. © 2013 IEEE.

Vivekanandan S

Department of Instrumentation

School of Electrical Engineering

Vellore Campus

Koleti A

Devanand M.

Vellore Institute of Technology (VIT) is a private university located in&nbsp;Tamil Nadu, India. Founded in 1984, as Vellore Engineering College, the institution offers 20 undergraduate, 34 postgraduate, four integrated and four research programs. It has campuses in Vellore, Amravati, Bhopal and Chennai.

VIT is one of the top ranked private universities in India according to NIRF, THE and QS Rankings.&nbsp;Govt. of India has recognized&nbsp;VIT, Vellore as an&nbsp;Institution of Eminence. This has allowed VIT to take independent quality initiatives and move up in world ranking.

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VIT University

2013 Nirma University International Conference on Engineering (NUiCONE)

This paper proposes a low cost intelligent system for monitoring, control, safety and security of industries. The monitoring system incorporate sensors like temperature, gas, ultrasonic, current and voltage, which screen parameters continuously and send data to a remote server using a ZigBee module for real time inspection. The monitored data log is stored in spreadsheet and can be updated to a cloud. The system has also utilized Red Tacton, a NFC based device which uses human touch to capture data and viewing can be done using a wearable or laptop. When abnormal readings are received, suitable actions and alerts are triggered by the server. This system can also control the appliances from a remote server laptop/computer. The security framework includes a password based door lock with facial recognition based authentication log. Door can be opened/closed using a passkey or through a mobile/web application. Facial recognition system uses CNN algorithm to recognize faces of employee and update their entry/exit details into a database. If an intruder tries to break in, an email alert is sent to the respective officials for action. © 2018 IEEE.

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Journal	Data powered by Typeset2013 Nirma University International Conference on Engineering (NUiCONE)
Publisher	Data powered by TypesetIEEE
Open Access	No