The increasingly widespread use of smart devices in conjunction with cameras and various sensors, such as temperature sensors, motion sensors or CO2 sensors, that enables complex monitoring and detection of events and conditions in real time. This combination enables effective use in areas such as intelligent lighting, air quality data collection, traffic management and waste management.
Sensor networks provide an extensive base for real-time monitoring and event processing. They can quickly detect problems, anomalies and dangerous situations. By analyzing historical data, it is possible to automate processes, optimize performance and uncover patterns and relationships that would escape human observation. Predictive analytics allows for forecasting of future events in order to take preventive action.
The use of artificial intelligence algorithms is essential for processing large volumes of sensor data. Specialised AI models process this data efficiently and can be implemented directly in the device. This allows the system to work in a decentralised way and increases its efficiency. The data obtained from the sensors can be integrated into a digital twin, which is analysed using AI algorithms. This enables rapid response to changes, improving system efficiency and simulating different scenarios for better decision making.