Higher Data Collection vs Network Bandwidth
Deploy edge computing to pre-process and filter sensor data locally, transmitting only operationally significant events to reduce bandwidth and cloud costs.
CyberTRIZ analysis · SmartCity contradiction C13-SC003 · one of 8,235 worked contradictions published by CyberTRIZ.AI
Regulations
Business Context
IoT devices continuously generate operational information regarding traffic, utilities, environmental conditions, public infrastructure, and municipal services. Collecting larger volumes of data improves situational awareness and supports Artificial Intelligence applications. However, transmitting every data point across municipal communication networks increases bandwidth requirements, communication costs, latency, and energy consumption. Municipalities must maximize operational intelligence while preserving network efficiency.
Smart CityTRIZ Resolution
Instead of transmitting all sensor data continuously, municipalities should deploy edge computing that processes information locally, transmitting only relevant events, summarized information, or operational exceptions to centralized platforms.
Applicable TRIZ Principles
Principle 2 – Taking Out removes unnecessary information before transmission.
Principle 20 – Continuity of Useful Action processes operational data continuously at the network edge.
Principle 28 – Mechanics Substitution replaces centralized processing with distributed intelligent computing.
Expected Outcome
Reduced network utilization
Faster operational response
Lower communication costs
Improved scalability
Decision Indicators
Early indicators that IoT communications require optimization include:
Network congestion becomes more frequent.
Communication latency increases.
Cloud storage costs grow rapidly.
Large volumes of redundant sensor data are transmitted.
Edge devices remain underutilized.
Monitoring these indicators supports efficient IoT communications.