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Stream/Area:
-
Subject:
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Paper ID:
IJSREM65287
Volume:
10 |
6 |
Jun 2026
Pages:
1-20
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Computer Science and Engineering
Jagannath University Jaipur
Computer Science and Engineering
Jagannath University Jaipur
Computer Science and Engineering
Jagannath University Jaipur
The growth of surveillance systems in private places has created a big need for systems that can automatically watch and analyze video feeds as they happen. Traditional surveillance systems mostly rely on people watching the videos all the time which's not very efficient and can lead to mistakes. Security people often have to watch camera feeds at the same time, which increases the chance of missing important events like suspicious activities or threats from weapons. Also old surveillance systems that just look for motion often give alarms because of changes in the environment like light or shadows. These problems show that we need a system that can automatically watch and analyze video feeds in real time. This paper is about a surveillance system that uses Artificial Intelligence to detect people and weapons. The system uses a model called YOLOv8 to detect people and weapons in real time from many video sources like webcams CCTV footage and recorded videos. The system always looks at the video frames detects objects and identifies activities. It also sends alerts when it finds something dangerous or unusual. This system is better than surveillance methods because it does not need people to watch the videos all the time and it can detect things faster. The surveillance system has parts including video acquisition, frame preprocessing, object detection, crowd counting and automated alerts. The preprocessing part makes the video frames better so that the system can detect things accurately. The YOLOv8 model then looks at the frames. Finds objects like people and weapons. The system is trained to detect people and weapons which's very important for public safety. To make the system more useful it also has a hardware alert mechanism that uses Arduino UNO. When the system detects something it sends an alert stores the information in the cloud and sends an email to the administrator with a picture of the threat. The system also has a web dashboard where the administrator can see what is happening in time and get reports. The cloud database stores all the information about the surveillance. The system was tested in different situations and it worked very well. It could detect people and weapons quickly and accurately. The crowd counting and suspicious activity monitoring parts made the system even smarter. The results show that Artificial Intelligence can really improve safety and make surveillance more efficient. The system can be used in places like airports, schools and shopping malls. In the future we can add features, like thermal imaging and facial recognition to make the system even better.
KEYWORDS
The OBJECTIQ system is really good at detecting things. It uses Artificial Intelligence and Computer Vision to watch what is going on and find problems. The OBJECTIQ system is connected to the Internet. Uses cloud technology. This means the OBJECTIQ system can watch things at the time and send alerts if something bad is happening. The old way of watching security cameras was not very good. People had to sit and watch the cameras all the time. This was boring. People would get tired. They might miss something. The old system was also slow to respond to problems. The OBJECTIQ system is better. The OBJECTIQ system can watch the cameras all the time without getting tired. The OBJECTIQ system can find problems. Send alerts. This means that people can respond quickly to emergencies. The OBJECTIQ system is a way to keep people safe. The OBJECTIQ system can watch cameras at the time and find problems before they become big issues. The OBJECTIQ system is a way of doing surveillance. The OBJECTIQ system uses Artificial Intelligence to make things better. The OBJECTIQ system is very good at finding events. The OBJECTIQ system can do this in time. This means that people can respond to problems away. The OBJECTIQ system is an improvement over the way of doing things. The OBJECTIQ system is a way to keep people safe. The OBJECTIQ system is a way of doing surveillance. The OBJECTIQ system was made using technologies like Python, OpenCV, YOLOv8, Flask, MongoDB Atlas and Arduino UNO. The YOLOv8 model is the core of the OBJECTIQ system. It is used for object detection. The YOLOv8 model is fast. Can find objects quickly. The OBJECTIQ system can watch cameras at the same time. It can find people, weapons and suspicious objects. The OBJECTIQ system can watch webcams, video files and live streams from IP cameras and CCTV systems. One of the things about the OBJECTIQ system is that it can detect objects in real-time. The OBJECTIQ system can also analyze crowds. Find suspicious activity. The OBJECTIQ system can count the number of people in a crowd. It can update the numbers in time. This is useful for safety. The OBJECTIQ system can be used in airports, railway stations, shopping malls and schools. The OBJECTIQ system can also detect activity. If it finds something it will send an alert. The OBJECTIQ system is better than surveillance systems. Old systems record video. The OBJECTIQ system takes action away. It can send emails update the dashboard and activate hardware devices. The OBJECTIQ system uses devices. These devices can communicate with the OBJECTIQ system. They can send alerts and warnings. The OBJECTIQ system can turn on lights and buzzers. It can display warning messages on screens. This is useful for emergency situations. The OBJECTIQ system has a web dashboard. This dashboard is user-friendly. It shows video feeds. It shows detection results. The dashboard is useful for administrators. They can manage the OBJECTIQ system. They can configure settings. Generate reports. The OBJECTIQ system uses a database. This database is called MongoDB Atlas. It is scalable and secure. The OBJECTIQ system can store detection logs and event history. It can store user records and alert information. The OBJECTIQ system can generate reports in PDF and CSV formats. The OBJECTIQ system is fast and accurate. It can detect objects in time. The OBJECTIQ system is better than surveillance systems. It is suitable for public safety environments. The OBJECTIQ system can be used in places. It can be used in cities and smart homes. The OBJECTIQ system has some limitations. It can be affected by lighting and low-resolution video feeds. It can be affected by motion blur and crowded scenes.. The OBJECTIQ system is still reliable. It can detect objects. Send alerts. The OBJECTIQ system can be improved in the future. It can be integrated with AI technologies. It can be used for recognition and anomaly detection. The OBJECTIQ system can be used for traffic monitoring and industrial automation. It can be used for wildlife surveillance and border security. The OBJECTIQ system is an example of how Artificial Intelligence can improve public safety. The OBJECTIQ system can reduce security risks. It can improve monitoring efficiency. The OBJECTIQ system can reduce workload. It can increase the ability to respond quickly during emergency situations. In conclusion the OBJECTIQ system is a time intelligent surveillance framework. It can detect objects and analyze crowds. The OBJECTIQ system can send alerts and warnings. It is an intelligent surveillance solution. The OBJECTIQ system is suitable, for public safety environments.
1. James Connan, Dane Brown, Marc Marais, and Luke Goodal, ”2025. Real- Time Gun and Person Detection for Smart Surveillance”. In 2025 International Conference on Artificial Intelligence, Big Data, Computing and Data Communication Systems (icABCD 2025), November 26–27, 2025, Cape Town, South Africa. ACM, New York, NY, USA, 9 pages. https://doi.org/10.1145/3759023.3759128. 2. Niranjana J., Mary Dhivya J., Balamurali A., “Artificial Intelligence Powered Weapon Detection with Automated Threat Alert System,” Proceedings of ICSICE, 2025. 3. Thangavel Murugan et al., “AI-Based Weapon Detection for Security Surveillance: Recent Research Advances (2016–2025),” Electronics, 2025. 4. Amit Kumar, “OBJECTIQ – Intelligent Object Detection System,” Github repository , 2026. https://github.com/CsWithAk/Object_IQ.git
Publication Date
6/23/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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