UP2Smart's main goal is developing a complete system for smart cities management based on data mining, computer vision and machine learning techniques to solve different types of problems. The envisioned system for smart cities management will have different modules as follows:
Automatic detection and classification of damaged sectors in the road/railways:the system will be used to automatically detect and classify deteriorated parts in the roads through a smart vision system. For example, the system will evaluate the condition of the asphalt and the visibility in the painting of the division lines. This will help to have information in real time about the deterioration level in the roads.
Abnormal events detection :This module will detect, quantify and report the abnormal events in order to improve safety. For instance, automatic detection of prohibited actions. The system will be also able to estimate the duration of the abnormality in the dangerous zone. If the event takes longer than a predefined threshold, an alert will be sent to a central control room. For example, if a car or a person stops on the crossing railways/tramway for a long time (more than 1 min), the system will send an alert to the central control room to avoid accidents.
Smart parking system :The system will provide the functionality of smart parking by monitoring the locations of empty spots in public parking places in order to quickly direct drivers using the mobile application of the system to reach open spots.
Traffic congestion detection on the road :our vision system based on real-time video analysis can be able to detect the density of the vehicles on the lane with the speed of vehicles. Our system will guide the drivers according to the current condition of the traffic flow and propose the new paths to out from this congestion.
Urban Air Pollution Monitoring system :our system will monitor urban air pollution use sensor-based instruments in place of cameras used for monitoring the road quality and smart parking.
The system will provide statistical information and intelligent predictions and recommendations as explained below:
1. Cost Reductions and quicker effective decisions using real-time information: The system will provide to the stakeholders (i.e. governmental administrations) real-time useful information to enable them to take quick and effective decisions. For instance, according to the current condition of the roads, the system will recommend if needed, the priority order to repair the damage sectors according to available data. Thus, the system is also envisioned to predict the total cost of repairing the damaged sector and comparing it with the cost provided by different companies specialized in road repairing that wants to use the system to make an offer.
2. Automatic prediction of relevant information needed for stakeholders to take right decisions: For instance, the system can predict the deterioration in the roads in order to recommend preventive maintenance.
3. Automatic assignation of the available budget: For instance, the stakeholders can use the system to transparently use the available budget according to the priority given to the reparation of the road damage detected. This will avoid corruption in the assignation of contracts.