| Titre : | Smart Traffic Light System For Smart Cities |
| Auteurs : | Fatiha Helal, Auteur ; Yahia Mohamed Boudjoras, Auteur ; Mahi, Faiza, Directeur de thèse |
| Type de document : | texte manuscrit |
| Editeur : | Université mustapha stambouli de Mascara:Faculté des sciences exactes, 2023 |
| ISBN/ISSN/EAN : | SE02343T |
| Format : | 75P. / couv. ill. / 29cm. |
| Accompagnement : | disque optique numérique (CD-ROM) |
| Langues: | Anglais |
| Résumé : |
The rapid development of technology, economy and population growth cause most transportation vehicles to be used in today's cities. Using more vehicles causes long queues at traffic lights, unnecessary waste of time, unnecessary fuel consumption while waiting at traffic lights and nature pollution. In this study, it is to create an intelligent traffic light based on image pro-cessing technology, using Python, YOLO, Genetic Algorithm AG and Particle Swarm Optimization PSO, where the traffic light knows the number of vehicles available in addition to the number of pedestrians, depending on these numbers the timers of traffic light will be changeable and this reduces the unnecessary waiting time. At the end of the search, the results have proven the superiority of the Ge-netic Algorithm traffic light has been compared with PSO Algorithm. Keywords: Intelligent Traffic Light, YOLO, Genetic Algorithm, PSO |
Exemplaires (1)
| Code-barres | Cote | Support | Localisation | Section | Disponibilité |
|---|---|---|---|---|---|
| SE02343T | INF929 | Livre audio | Bibliothèque des Sciences Exactes | 7-Mémoires Master | Consultation sur place Exclu du prêt |
Aucun avis, veuillez vous identifier pour ajouter le vôtre !
Accueil
