Description

AI & IoT Smart City - Environmental Hazards and Waste Optimization

Project Proposal
Project Title
AI & IoT Smart City – Environmental Hazard Monitoring and Real-Time Waste Collection Optimization
General Description
This project aims to develop an end-to-end Smart City prototype for real-time monitoring and management of environmental hazards and urban waste.
The system will combine IoT sensor networks and Computer Vision to identify and monitor various types of urban hazards, including safety hazards, sanitation issues, infrastructure and water-related problems, and environmental and natural hazards.
The system will collect data from IoT edge devices and cameras, transmit the information to a central server, and display detected hazards and waste-related information on a smart dashboard. The system will also support real-time optimization of municipal waste collection operations.
Project Scope
The project focuses on developing an integrated Smart City system that combines IoT, Artificial Intelligence, Computer Vision, and optimization algorithms.
The system will include:
•	IoT Monitoring: Edge devices such as Raspberry Pi and ESP32 equipped with ultrasonic distance sensors for monitoring the fill level of waste bins.
•	AI & Computer Vision: Use of AI models such as YOLOv8 to automatically identify hazards, including illegal waste dumping, from surveillance cameras.
•	Data Communication: Transmission of sensor and detection data to a central server using the MQTT protocol.
•	Smart Dashboard: Presentation of detected hazards and waste-related information on an interactive map-based dashboard.
•	Waste Collection Optimization: Use of collected information to support automatic calculation of efficient collection routes for municipal waste collection trucks.
•	End-to-End Integration: Integration of sensors, AI-based detection, communication, backend processing, dashboard visualization, and waste collection optimization into a single prototype.
The system may monitor different categories of urban hazards, including:
•	Safety hazards such as potholes, damaged sidewalks, and traffic light failures.
•	Sanitation hazards such as accumulated waste, animal carcasses, and cleanliness issues.
•	Infrastructure and water-related issues such as street lighting failures, water leaks, and sewage problems.
•	Environmental and natural hazards such as stray animals, fallen trees, and noise or odor hazards.
Student Requirements
•	Teamwork
•	Full participation in weekly meetings
•	High motivation and commitment
•	Independent learning
•	Personal responsibility
•	Interest in Artificial Intelligence and IoT technologies
•	Ability to learn and work independently with new technologies
•	Ability to work with multiple system components and integrate them into an end-to-end solution
Development Tools
•	Python
•	YOLOv8
•	Computer Vision
•	OpenCV
•	Raspberry Pi
•	ESP32
•	Ultrasonic sensors
•	IoT
•	MQTT
•	Backend server
•	Database
•	Interactive map / GIS dashboard
•	Optimization algorithms
•	GitHub
Deliverables
•	Working End-to-End Prototype: An integrated system combining IoT sensors, AI-based hazard detection, data communication, backend processing, and dashboard visualization.
•	AI-Based Detection System: A working Computer Vision component capable of identifying selected urban hazards from camera footage.
•	IoT Monitoring System: Working edge devices and sensors for monitoring waste bin fill levels.
•	Smart Dashboard: Interactive map-based dashboard displaying detected hazards and waste-related information.
•	Waste Collection Optimization: Integration with the existing waste collection route optimization system and demonstration of the extended functionality.
•	GitHub Repository: Complete and documented source code.
•	Final Presentation
•	Academic Poster
•	Demonstration Video
Additional Notes
This project is an extension of an existing student project supervised by Netanel Zohar, which automatically calculates efficient waste collection routes for municipal waste collection trucks.
The new project will build upon the existing system and expand its capabilities by adding real-time environmental hazard monitoring, IoT-based waste bin monitoring, AI-based Computer Vision, and a smart municipal dashboard.
The project is intended as an end-to-end Smart City prototype combining multiple technologies and system components.
AI & IoT Smart City - Environmental Hazards and Waste Optimization

Full Stack

Description

Emphasis in project execution

The project is has cooperation with the industry and combines meeting deadlines while being creative and focused on the task

THE PROJECT IS AT FULL CAPACITY
