RIDING BY FACE SCAN SYSTEM
| What assumptions (if any) are you making? | |||||
| Whether the public accepts face recognition, especially the elderly peopleComputer-drivenfacial recognition as an emerging technology which will transform the transport sector and other private and public sector in Nottingham. Many people are broadly welcoming it in society. Nevertheless, some groups have a rising concern concerning the place of facial recognition technology in self-governing society(Signor et al., 2018). Imperatives being raised include issues of diminished accountability, compromised civil rights, and limitation on concentration power. Public wise, especially the elderly, have raised concerns on the large scale misidentification and the machine bias in the form of systematic misrecognition by skin color or ethic. Whether the payment process is safe and reliableThe face scan riding technology payment process among passengers will be safe, reliable, and easy to manage. The processing of fare tickets to the passenger will also be simplified and timely. The facial recognition implementation on the purchase of a ticket will consider people with different facial disabilities. Although there are chances of system cybercrime interference on customers’ accounts, quick alerts will prevent loss of passenger cash due to system hacks. Therefore the system will be safe for a different group in society, including the children. Is it suitable for densely moving people, such as subway stations, railway stations, ETC?The use of innovative technology, such as the face scan riding system in transportation, will change and improve the transport sector in Nottingham. Nottingham urban centers with highly populated will be able to book transport means in advance through the face recognition system. Despite the challenge that citizens may the first experience in its implementation, facial recognition will be reliable, safe, and convenient for densely moving people due to system availability. Face scans will save time in terms of buying tickets and boarding transport modes such as trains, airlines, and vehicles.
| |||||
| Are there any significant problems you are aware of? | |||||
| The face scan riding system has several challenges, which include pose variation, absence of structuring elements such as beard, facial expression change, aging of the face, varying illumination condition, image resolution, and mobility, availability, and quality of face dataset such twin(Fischer. 2019). These are common challenges that will affect the implementation of the face recognition system. The system, at times, will fail to identify the registered individuals. This will pose a problem when passengers are buying and boarding vehicles, especially the aged and twins. If there is a mechanical failure in the face recognition process, are there alternative tools for subsequent payment processes to avoid small-scale personnel retention. The solution to the mechanical failure of a face scan riding system is rectified in various ways. First, the system needs to consist of a two-step process. That is facial feature extraction and facial feature matching against an available database(Siddiqui et al. 2020). The other development that can be accommodated in the system includes Eigen face, active appearance model, shape and face texture, and local binary patterns by creating a local texture descriptor. This will make the individual prepare and process payment efficiently without cash loss. It will also help identify and differentiate twins and people who look alike in Nottingham’s face scan-riding system.
| |||||
| Are there any specific conditions or constraints? | |||||
| When face recognition, there must be no cover on the face(Moon et al. 2017). Also, people with prosopagnosia may face challenges when using a facial recognition system. The condition is a result of the right fusiform gyrus of the brain. Other requirements that face scan riding modes require include a bright face with no beard, frontal pose control, control of illumination, uniform background, and neutral expression. All this condition must be met to enhance facial recognition of the person by the face scan riding system.
| |||||
| Who will you need to carry out this project? | |||||
| Face recognition projects will benefit different manufacture and individual in society. These stakeholders include phone manufacture for unlocking phones, detective to track missing persons, a forensic investigator by aiding face identification, and in school to prevent treats and monitoring school attendance(Bolotnikova et al., 2017). The face recognition system will also be used in the casino to identify gamblers’ entrance, facilitate safe transactions in the face, control access to the sensitive area, and improve air transport more conveniently (Potdukhe and Pawar. 2019). Therefore, the face scan system will improve and play an essential role in the development of Nottingham cities and transport sectors. The innovation will facilitate security across all areas of the economy in Nottingham.
| |||||
| Completed on | Completed by | Agreed by | |||
|
| |||||
References
Xiong, X., 2018, January. Research and development of face recognition system based on ARM architecture. In 2018 International Conference on Intelligent Transportation, Big Data & Smart City (ICITBS) (pp. 113-116). IEEE.
Sukhija, P., Behal, S., and Singh, P., 2016. Face recognition system using a genetic algorithm. Procedia Computer Science, 85, pp.410-417.
Siddiqui, M.F., Siddique, W.A., Ahmedh, M., and Jumani, A.K., 2020. Face Detection and Recognition System for Enhancing Security Measures Using Artificial Intelligence System. INDIAN JOURNAL OF SCIENCE AND TECHNOLOGY, 13(09), pp.1057-1064.
Moon, H.M., Seo, C.H. and Pan, S.B., 2017. A face recognition system based on a convolution neural network using multiple distance face. Soft Computing, 21(17), pp.4995-5002.
Bolotnikova, A., Demirel, H., and Anbarjafari, G., 2017. Real-time ensemble based face recognition system for NAO humanoids using a local binary pattern. Analog Integrated Circuits and Signal Processing, 92(3), pp.467-475.
Signor, K., Kumfer, W., LaJeunesse, S., Carter, D., Smith, W., Scaringelli, M., and Deans, S., 2018. Safe Systems Synthesis: An International Scan for Domestic Application.
Potdukhe, A.A. and Pawar, S.S., 2019. Study on: Advancement of Smartphone Security by using Iris Scan Detection.
Fischer, H., Innovative Dragon Ltd, 2019. The transport system, self-driving vehicle, and control method of a transport system. U.S. Patent Application 16/317,664.
Corcoran, P., Fotonation Ltd, 2018. Multi-camera vision system and method of monitoring. U.S. Patent Application 15/591,321.
Corcoran, P., FotoNation Limited, 2018. Methods for detecting, identifying, and displaying object information with a multi-camera vision system. U.S. Patent Application 15/591,434.