Urban sensing encompasses a diverse set of technologies that collect information about physical space and human activities in urban areas. Let’s delve into the details with examples:
- Urban Objects and Properties to Be Sensed:
- Urban Objects: These include various elements within the city, such as:
- City Infrastructure: Roads, bridges, and public transportation systems.
- Buildings: Detecting their presence, geometry, and stability.
- Land Cover and Land Use: Identifying green spaces, residential areas, commercial zones, etc.
- Individuals: Tracking people’s movements and activities.
- Properties to Be Sensed:
- Static Properties: These remain relatively stable over time, e.g., building existence, land cover.
- Dynamic Properties: These change frequently, e.g., car trajectories, land use changes.
- Technologies for Urban Sensing:
- Satellite-Based Sensing:
- Optical or InSAR Images: Satellites capture high-resolution images of urban areas from space.
- Airborne Sensing:
- LiDAR and Optical Images: Aircraft-mounted sensors provide detailed 3D data.
- Digital Signals: Gathered from aircraft or UAVs.
- Ground-Based Sensing:
- Mobile Mapping Systems: Cars equipped with laser scanners collect street-level data.
- Ground-Penetrating Radar (GPR): Detects underground utilities.
- Underwater Sensing:
- Multi-Beam Sonar Sensors: Used on boats to map underwater terrain.
- Individual Sensing:
- Mobile Phones: Provide indoor/outdoor location data.
- Wearable Devices: Measure properties like body temperature.
- Data Usage:
- Spatial, Temporal, and Attribute Data: Urban sensing generates rich datasets.
- Urban Analytics: These data inform city planning, transportation optimization, and emergency response.
- Urban Service and Governance: Decision-makers use insights for better urban management.
Urban sensing plays a crucial role in creating smarter, more efficient cities by harnessing technology to understand and improve our urban environments. Urban sensing technologies are significantly influenced by techniologies like edge computing, the Internet of Things (IoT), and sensor networks:
Edge Computing:
- Definition: Edge computing refers to processing data closer to its source (devices or sensors) rather than in centralized data centers.
- How It Works: Edge servers or devices process information locally, reducing latency and improving real-time responsiveness.
- Example: Consider a smart traffic management system. Traffic cameras at intersections analyze video feeds locally to detect congestion, accidents, or rule violations. Only relevant data (e.g., an accident alert) is sent to the central system for further action.
Internet of Things (IoT):
- Definition: IoT connects everyday objects (devices, vehicles, appliances) to the internet, allowing them to collect and exchange data.
- How It Works: Sensors embedded in IoT devices capture data (temperature, humidity, motion) and transmit it wirelessly.
- Example: Smart waste bins equipped with IoT sensors monitor fill levels. When a bin is full, it sends an alert to waste management teams for timely collection.
Sensor Networks:
- Definition: Sensor networks consist of interconnected sensors deployed in a specific area (e.g., a city).
- How It Works: Sensors collaborate to collect data on environmental conditions, traffic flow, air quality, etc.
- Example: Urban air quality monitoring networks deploy multiple sensors across the city. These sensors measure pollutants and provide real-time data for health advisories or policy decisions.
For Further reading refer -> https://link.springer.com/chapter/10.1007/978-981-15-8983-6_19
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