An Embedded system based security service in smart cities
This project proposes a Lightweight Age invariant based Face Recognition System to Enhance Security Services in Smart Cities. Age invariant face recognition faces many challenges due to age-related biological transformations in presence of the other appearance variations. A change in user preference
Project Title
An Embedded system based security service in smart cities
Project Area of Specialization
Project Summary
This project proposes a Lightweight Age invariant based Face Recognition System to Enhance Security Services in Smart Cities. Age invariant face recognition faces many challenges due to age-related biological transformations in presence of the other appearance variations. A change in user preferences has been observed in recent years with the growth of embedded devices, so these devices can be used to assist law enforcement agencies more efficiently. Law enforcement agencies face problems when it comes to providing a cost-effective solution for surveillance and suspect detection. Security budgets are limited in third-world countries, so simple and cost-effective solutions are required to ensure public security. In the literature, deep learning methods are popular in face recognition but they require significant computing resources and storage due to the complex nature of convolutional neural networks (CNNs). These methods are difficult to deploy on mobile devices or embedded terminals and less suitable for real-time detection and recognition of suspects. Our proposed lightweight face recognition system is a step towards a cost-effective solution to enhance services for law-enforcing agencies regardless of time and place in smart cities.
Project Objectives
1) To investigate the various state-of-the-art techniques related to the lightweight face recognition system.
2) To develop a lightweight face recognition system based on age invariant features.
3) To deploy it on embedded devices such as Raspberry Pi.
Project Implementation Method
The project will be implemented in python (by using various sets of libraries) and supporting packages of Raspberry Pi for image processing on different data sets.
Benefits of the Project
1) Raspberry Pi based face recognition is an advanced technology, which can enable law enforcement agencies to easily identify different suspects locally irrespective of time and place.
2) Raspberry Pi based face recognition system can be easily mounted on police officer shirts, on the police van, or at any local place.
Technical Details of Final Deliverable
1) A camera attached to Raspberry Pi for real-time video streaming.
2) Face detection and recognition feature.
3) Display unit to show the results of suspect recognition.
Final Deliverable of the Project
Core Industry
Other Industries
Core Technology
Other Technologies
Sustainable Development Goals
Required Resources
| Item Name | Type | No. of Units | Per Unit Cost (in Rs) | Total (in Rs) |
|---|---|---|---|---|
| Raspberry Pi 4 | Equipment | 1 | 35000 | 35000 |
| Camera | Equipment | 1 | 2000 | 2000 |
| Display Screen | Equipment | 1 | 12000 | 12000 |
| Total in (Rs) | 49000 |
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