Nowadays Security has become major concern for every company and institution. Every company either big or small is trying his best to secure data at any cost. Computer vision and artificial intelligence like technologies help us to achieve everything that we imagine and security is one of them. So,
Unknown People and their location Identifaction
Nowadays Security has become major concern for every company and institution. Every company either big or small is trying his best to secure data at any cost. Computer vision and artificial intelligence like technologies help us to achieve everything that we imagine and security is one of them. So, I am working on intruder and activity detection/identification and send alert email messages to authority using different AI and face detection algorithms. It will help almost every company to achieve security and secure his data. By using difference face and activity recognition models and algorithms it will detect particular person if that person does not belongs to that company then it will send alert email message to company’s authority. For example: most of the banks have locker room where only authorized person have access so, in case any unknown person or unauthorized employee enters in that room this system will detect him/her and will send automated alert email message to particular authority. It will track the location of that intruder that he/she is in in premises or not. Furthermore, it will also be used in universities for attendance system. It will fully automate the attendance system. It will recognize face of students and teachers and automatically mark the his/her attendance.
The main objectives of the projects are:
The above procedures can be summarized into 6 stages:
Stage 1: Research and analyze best recognition models and algorithms of computer vision and deep learning.
Stage 2: Sorting out the best model, algorithm and dataset
Stage 3: Training the model
Stage 4: Testing the model
Stage 5: Optimize it for better accuracy
Stage 6: Designing the UI
Stage 7: Registeration of Users and Generating the Dataset
Stage 8: Comparative analysis and Deployment
It will be easier and automated to identify unknown people that are not part of company/industry using this automated software. It will be cost efficient because you don’t need a lot of workforce like guards, security and separate camera monitoring teams. Security will be increased. It will also fully automate the system of student's attendance monitoring with just their face so, the transparency in attendance will be maintained.
This project aims to implement a fully functional software of smart surveillance system in which intruder is recognized and alert email is generated which is then sent to particular authority for security reasons. In this project a model is trained and tested on different datasets for classification of people. One shot Learning will be used that can be trained on low dataset and can be effective in identifying people. Web scraping will also be used to automate the whole attendance system. For email generation, API will be used to send the email to concerned authority. It will automatically recognized people that would part of organization other people would considered as intruder. You can not rely on camera monitoring teams all the time so it will remove the intervention of camera monitoring teams and transparency will be maintained. Cost will be reduced with that system. In this project, different models will be used and comparative analysis will be done on these model to check the best performing model on given conditions.
| Item Name | Type | No. of Units | Per Unit Cost (in Rs) | Total (in Rs) |
|---|---|---|---|---|
| NVIDIA Jetson Nano Developer Kit | Equipment | 1 | 34799 | 34799 |
| Hikvision 8MP IP Camera DS-2CD2185FWD-I | Equipment | 2 | 17570 | 35140 |
| Miscellaneous | Miscellaneous | 1 | 10000 | 10000 |
| Total in (Rs) | 79939 |
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