Editing Introduction to Edge Computing (section)

=== 1.3.4 Smart Cities & Infrastructure ===
Smart cities integrate edge computing for efficient urban management, security, and environmental monitoring. Data is processed locally to reduce network congestion and response times.

====Traffic Optimization: ====
Edge-enabled traffic systems use vehicle counters and cameras to assess road usage and adapt signal timings accordingly. Instead of relying on pre-set light cycles, these systems dynamically respond to real-time traffic conditions, reducing congestion and travel times. Edge processing ensures decisions are made locally and instantly, avoiding delays caused by sending data to distant servers.

====Crime Detection:====
Surveillance systems in smart cities often rely on AI-powered edge devices to detect suspicious behavior or recognize faces in real-time. Cameras equipped with edge processors can analyze video feeds to identify threats such as weapons, unauthorized access, or unusual crowd behavior. Once detected, alerts are sent to security personnel instantly. This enhances public safety while reducing the need for constant human monitoring.

====Waste Management: ====
Smart bins use edge sensors to detect fill levels and optimize pickup routes.

====Disaster Response: ====
Edge computing supports real-time disaster detection and response mechanisms in smart cities. Sensors for earthquakes, floods, or fires process data locally to identify threats and trigger immediate alerts or evacuations. By avoiding delays associated with cloud communication, these systems enable faster and more effective responses, saving lives and minimizing damage.