CNN Applied In Public Transport For The Protection Against The Covid-19 Spread
How to Cite?
Tahiry Karim, Remzan Nihal, Barik Sanaa, El Bouni Abderrahmane, El Asri Ayoub, Zouitine Omar, Farchi Abdelmajid, "CNN Applied In Public Transport For The Protection Against The Covid-19 Spread," International Journal of Engineering Trends and Technology, vol. 69, no. 10, pp. 33-37, 2021. Crossref, https://doi.org/10.14445/22315381/IJETT-V69I10P205
With the Coronavirus becoming a huge threat, the world is experiencing a very uncertain situation. In Morocco, especially after confinement, the number of cases has increased dramatically; this sudden increase is due to several factors, including public transport. This is where our project derives its interest, because thanks to the many alternatives it offers, it reduces the risk of contamination, which makes it possible to reduce the cases of illnesses linked to Covid-19 as well as to reduce the rate of accidents. To achieve our goal, the transport will be equipped with new technologies boosted by artificial intelligence and other tools, a passenger so that he can board the bus must be wearing a facial mask detected through an artificial intelligence-based mask detector. Covid-19 not only affects the physical health of the person, but it has a major impact on mental health, especially for drivers who are more involved to be infected by the virus. For this, there is an emotion recognition system based on AI and social intelligence that detects the emotions of the driver and generates actions that correct, regulate and stabilize their emotional state. A deep learning algorithm has been applied, and an accuracy rate of 91.23% was found in CNN with only 300 epochs.
Covid-19, Artificial Intelligence, Emotional Recognition, Social Intelligence, Deep Learning.
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