Building a Raspberry PI Car Safety System with Facial Recognition
Kharel, Shurakshya; Adhikari, Hari (2019)
2019
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-201904306886
https://urn.fi/URN:NBN:fi:amk-201904306886
Tiivistelmä
The final year project was about developing a prototype of a car security system with cognitive services, Internet of Things (IOT) and facial recognition Api. The aim of the application was to enhance safety of the car drivers and security from the possible thefts. In addition, the application also focused on making cars personalised and creating the safe and smooth journey for the users.
The project was carried out to build smart solution with safety-first mindset. Continuous monitoring of car drivers and analysing the response every possible minute is the key factor to ensure the car is driven in well manner. This was achieved with the integration of IOT devices and raspberry PI where backend server is continuously monitoring with the start of car. The application was developed on JavaScript based programming language. The scope of the project is limited to independent prototype of working system which is not integrated with car.
In conclusion, a functional working system was created using facial recognition and image analysis with Amazon Web Services, Open CV and different IOT devices such as PIR Motion Sensor and PI Camera Module. A robust application was built to collect data from the system and execute program on the basis of response in order to provide secure and risk-free drive experience to the user.
Hence, the face detection and emotion recognition-based system was successful to collect data to avoid possible thefts and road-accidents. Integration on car for such inbuilt-features would be huge future development.
The project was carried out to build smart solution with safety-first mindset. Continuous monitoring of car drivers and analysing the response every possible minute is the key factor to ensure the car is driven in well manner. This was achieved with the integration of IOT devices and raspberry PI where backend server is continuously monitoring with the start of car. The application was developed on JavaScript based programming language. The scope of the project is limited to independent prototype of working system which is not integrated with car.
In conclusion, a functional working system was created using facial recognition and image analysis with Amazon Web Services, Open CV and different IOT devices such as PIR Motion Sensor and PI Camera Module. A robust application was built to collect data from the system and execute program on the basis of response in order to provide secure and risk-free drive experience to the user.
Hence, the face detection and emotion recognition-based system was successful to collect data to avoid possible thefts and road-accidents. Integration on car for such inbuilt-features would be huge future development.