International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395-0056
Volume: 09 Issue: 04 | Apr 2022
p-ISSN: 2395-0072
www.irjet.net
IoT Based Smart Surveillance and Automation Milind R. Rampure1, Kevin P. Rathod2, Kashyap M. Pandya3, Pradnya V.Kamble4 123Students,
Department of Electronics and Telecommunication Engineering, K. J. Somaiya Institute of Engineering and Information Technology, Mumbai, Maharashtra, India . 4Assistant Professor, Department of Electronics and Telecommunication Engineering, K. J. Somaiya Institute of Engineering and Information Technology, Mumbai, Maharashtra, India. ---------------------------------------------------------------------***---------------------------------------------------------------------
Abstract - In this paper, we introduce a compact and
There is a requirement for a savvy and astute framework that is ought to identify any vindictive action and quickly report to essential individuals to carry out responsive actions.
complete solution to this problem, all packed in single Raspberry Pi by implementing an effective object detection model using Machine Learning and integrating it with advanced Image Enhancement technology, opencv to detect any human activity even under adverse conditions, it will start recording only if a person or a movement is identified and stop recording once there is no movement. This technique will improve the system's efficiency in terms of reducing the storage needed for saving recordings, and reducing the processing and searching time in the recordings. Body temperature of the person is recorded, In case of increased body temperature readings it will trigger an alert system to notify the owner.
Since the corona outbreak, scanning body temperature has become the “new normal” to tackle the current Covid19 pandemic. There are many temperature guns available in the market, but none of them gives any alert or email notification to higher authorities to take action when the temperature exceeds a particular limit. A traditional security camera system provides excellent support to the security of any home or business but can entirely be expensive.
2. LITERATURE SURVEY
Key Words: Machine learning, Raspberry pi, OpenCV, IoT
Initially, many Security Systems such as RFID, OTP-based systems, and biometrics were used to prevent unauthorized access. But sooner, people realized merely preventing unauthorized access was not enough and there was a need to come up with systems that would aid in catching the intruder, while also unfolding their motives.
1. INTRODUCTION Video Surveillance systems have been an extremely essential part of security systems installed in all types of offices, schools, hotels, businesses and even people’s homes.
Similar PIR-based systems triggered camera and sensor networks on motion detection, then uploaded captures to the cloud server and sent alerts using GSM technology.
A real-time surveillance system is designed and realized by using Raspberry Pi. The cheap price, low power consumption, and the availability of open-source software are major merits of using Raspberry Pi in developing applications. Thus, it has been widely implemented in the development of IoT technology, as its reliability and available information on the Internet.
All of the above solutions were heavily hardware dependent which is subjected to high-risk failure. Also, these solutions usually require a PC along with Wi-Fi DSP Kit which should be continuously ON for 24 hours, this leads to higher power consumption and also involves additional charges for every alert being sent.
Recent cameras that record when a movement is detected save storage rather than recording all the time. These new features of recording methods in the recent cameras indeed have affected its prices. Even though recording videos depending on detecting a movement has enhanced the efficiency of the surveillance system, it still consumes large storage. Thus, the need for a camera that records only humans has emerged. We will interface an IR temperature sensor and send the email alerts with the image of the person if the temperature of any particular person exceeds the set value.
© 2022, IRJET
|
Impact Factor value: 7.529
3. Our Proposed Method The smart system is based on Raspberry Pi 3B adopts the Internet of Things architecture and combines several sensors and devices for room security to set up a safer environment. In this proposed system, we introduce a compact and complete solution to this problem, all packed in a single Raspberry Pi by implementing an effective object detection model using Machine Learning and integrating it with advanced Image Enhancement technology and OpenCV libraries to detect only human activity even under adverse conditions. MLX90614 IR
|
ISO 9001:2008 Certified Journal
|
Page 3253