Meter Data Collection via Cellular Network Behavior Scheduling
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Solution Overview
Problem
Current methods for collecting data from communicating meters, such as smart electricity, water, or gas meters, often lead to network congestion and inefficient use of cellular communication resources, especially when meters are temporarily unavailable or out of range.
Innovation Solution
A method that involves obtaining behavior information from communicating meters, establishing parameters representing each meter's behavior, scheduling data collection based on these parameters, and transmitting data collection messages accordingly, thereby optimizing data collection and reducing network resource usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data collection is performed from all meters continuously, then complete data coverage is achieved, but network congestion occurs and network resources are wasted
Solution Approach 1:
The system changes the parameter of data collection timing by establishing behavior parameters (response time, availability patterns) for each meter and scheduling collections based on these parameters. This allows the system to adapt collection timing to each meter's behavior, achieving complete data coverage while minimizing network resource usage by avoiding redundant collection attempts during periods when meters are unavailable.
2Reliability
If data collection is repeated for meters that fail to respond, then data completeness is improved, but network congestion worsens
Solution Approach 1:
The system performs preliminary action by establishing behavior parameters for each meter in advance, including their response patterns and availability characteristics. Based on this pre-established information, the system creates an optimized collection schedule that predicts the best times to collect data from each meter, thereby improving success rate while avoiding redundant retry attempts that would congest the network.
3Use of energy by moving object
If meters are put on standby between operations, then energy consumption is reduced, but data collection timing becomes unpredictable
Solution Approach 1:
The system applies feedback by monitoring and establishing behavior parameters from actual meter responses over time. This includes tracking response times, availability patterns, and successful collection windows. The system then uses this feedback information to optimize future collection schedules, adapting to the meters' standby patterns while predicting optimal collection timing, thus resolving the timing unpredictability issue without requiring meters to remain constantly active.
Data Source
AI summary
A method for collecting, via a communication network of the cellular type, data available in a set of communicating meters, the method being implemented in a data collection system connected to said network and the method including: obtaining first information representing the behaviour of said meters; establishing parameters representing the behaviour of each of the communicating meters from said first information; establishing a scheduling for collecting data from all or some of said meters from said parameters representing the behaviour of each of the meters, and transmitting data collection messages to said meters for which said scheduling was established. The invention also relates to a data collection system configured to implement the method.