| Student Name | School | Degree | Year | |
|---|---|---|---|---|
| Faizan Ahmad | MCS | Undergraduate | Fourth | [email protected] |
| Muhammad Umar Nawaz | MCS | Undergraduate | Fourth | [email protected] |
| Muhammad Hammad | MCS | Undergraduate | Fourth | [email protected] |
| Muhammad Momin Abbas | MCS | Undergraduate | Fourth | [email protected] |
| Inter School Idea ? | No |
| Do you need expertises from another area: | No |
| If Yes please provide details of expertises you need: |
| Idea Name: | Autonomous Computational Intelligence-based Security and Surveillance System (AISS) |
| Slogan: | Vigilance, reliability, and security |
| Supervisor Name: | Col. Dr. Imran Makhdoom |
| Supervisor Designation: | RVF / Associate Professor |
| Supervisor School: | MCS |
| Supervisor Department: | Department of Information Security |
| Contact number: | 051-330404 |
| Email ID: | [email protected] |
| Abstract: | |
| Employing the emerging technologies of computer vision and machine learning in our surveillance systems. We are proposing a system AISS that autonomously detects perimeter intrusion using gesture recognition. AISS will quickly raise an alarm and notify security staff on any perimeter intrusion, eliminating the likelihood of human error and fatigue. | |
| What is the unmet need in society that your idea will fulfill ? | |
| The primary focus of using a camera is surveillance of an area. The issue faced is that an individual must watch the live feed and report the authorities in case of a breach or potential threat. So, we are training a machine learning algorithm which will detect anomalies. Therefore, this will reduce | |
| Who needs it ? How many would benefit ? | |
| Educational institutions, hospitals, law enforcement agencies, borders, city public areas, and the banking sector. | |
| How will the solution works | |
| The solution that we are providing basically uses a machine learning algorithm. The input for this algorithm is the live video or footage from closed-circuit television cameras around the premises. The trained algorithm will extract features from the input live videos and detect if there is any suspicious or anomalous activity happening in real time. The algorithm will generate an alarm that will alert the authorities. | |
| Who are your competitors ? How is your solution different | |
| The security and CCTV-provider companies are our competitors. Mostly, those solutions do object detection upon which the security staff would monitor that certain feed only, but still, it requires an extensive human effort to monitor and notify, if an anomaly occurs. | |
| Status: | new |
| Entry Date & Time: | 2022-12-13 (1623) |