Wildfire Sensor Network Configuration for LoRa Mesh Power Control
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Solution Overview
Problem
Existing wildfire detection systems face limitations such as limited coverage, high power consumption, scalability issues, and vulnerability to network failures, particularly in star and mesh topologies, leading to inefficient data transfer and security threats.
Innovation Solution
A system utilizing a mesh network topology with LoRa and LoRaWAN protocols, including data processing devices with sensors for environmental data collection, time synchronization, and a network configuration server for optimizing network architecture, enabling efficient data transmission and security through duty cycling and reduced idle listening.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If star topology network protocol is used for wildfire detection, then network configuration is simple, but power consumption is high and coverage is limited
Solution Approach 1:
The patent implements dynamic topology adaptation where the network automatically transitions between star and mesh topologies based on real-time conditions. When nodes have sufficient power, the system dynamically forms mesh connections to extend coverage and reduce individual node power consumption through distributed routing, while maintaining star topology simplicity when power is constrained.
Solution Approach 2:
The system changes network parameters dynamically by adjusting transmission power levels, routing protocols, and topology structure based on environmental conditions, battery status, and fire detection priorities. This allows the network to optimize between power consumption and coverage area by modifying operational parameters in response to changing conditions.
2Reliability
If mesh network topology is used for wildfire detection, then coverage and reliability are improved, but power consumption increases due to multiple active connections
Solution Approach 1:
The patent implements periodic duty cycling where mesh network connections are activated only during specific time intervals when fire detection is critical, rather than maintaining continuous active connections. Nodes alternate between active monitoring periods and low-power sleep periods, reducing overall power consumption while maintaining reliability during critical detection windows.
Solution Approach 2:
The system extracts and removes unnecessary mesh connections from the network topology, keeping only the essential redundant paths needed for reliability. By selectively maintaining only critical mesh links rather than all possible connections, the system achieves adequate reliability with significantly reduced power consumption compared to a fully connected mesh.
3Area of stationary object
If stationary sensors are deployed to expand coverage, then detection area increases, but system cost and installation time increase significantly
Solution Approach 1:
The patent replaces stationary sensors with mobile robotic platforms that can dynamically reposition themselves to cover different areas. Instead of installing fixed sensors throughout the entire coverage area, mobile robots move to strategic locations as needed, providing flexible coverage expansion without the high installation costs and complexity of deploying numerous stationary sensors.
Solution Approach 2:
The mobile robotic platform performs multiple functions including fire detection, navigation, and communication relay. A single mobile unit can cover multiple locations sequentially and also serve as a moving network node, replacing the need for multiple specialized stationary sensors and reducing overall system complexity and installation requirements.
4Ease of operation
If central hub is used in star topology, then network management is simplified, but single point of failure risk increases
Solution Approach 1:
The patent implements dynamic topology transformation where the network transitions from a static star topology with a central hub to a dynamic mesh topology when reliability concerns arise. The system automatically redistributes routing functions across multiple nodes, eliminating the single point of failure while maintaining simplified management through automated routing protocols that handle the increased complexity.
Data Source
AI summary
Provided are systems and methods for detection and network configuration. A system includes data processing devices and a server including a processor and a memory, the memory storing computer-executable instructions thereon that, when executed by the processor, cause the network configuration server to receive a plurality of synchronization and mapping messages from the plurality of data processing devices and the network gateway over a network for a predetermined period of time, determine a network architecture based upon the plurality of synchronization and mapping messages, the network architecture including a plurality of modes of operation of the plurality of data processing devices, a frequency channel for the plurality of data processing devices for transmission of environmental data, an optimization path, and an identity of a data processing device for transmission to another data processing device, and communicate the network architecture to the plurality of data processing devices over the network.