LoRa Mesh Wildfire Sensor Networking With Duty-Cycled Configuration
Find Innovative SolutionsGenerate Solutions
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
1Area of stationary object
If ground-based sensors use star or mesh network topologies for wildfire detection, then coverage area is improved, but power consumption increases significantly
Solution Approach 1:
The patent implements periodic action through duty cycling, where sensors transmit data at predetermined time intervals rather than continuously. The network controller manages transmission schedules, allowing sensors to remain in low-power states between transmissions. This periodic transmission approach enables extended coverage area while significantly reducing overall power consumption compared to continuous operation.
Solution Approach 2:
The system dynamically adjusts network topology and transmission parameters based on detected wildfire conditions. When wildfires are detected, the network switches from low-activity monitoring mode to high-activity alert mode, dynamically reallocating power and bandwidth resources. This dynamic adaptation allows the system to maintain comprehensive coverage during critical events while minimizing power consumption during normal operations.
2Loss of information
If ground-based sensors use traditional network protocols (Wi-Fi, Bluetooth, Cellular, Ethernet) for data transmission, then data transmission capability is improved, but power consumption increases due to higher transmission power and complex protocol overhead
Solution Approach 1:
The patent changes the fundamental parameters of network communication by switching from traditional high-power protocols (Wi-Fi, Bluetooth, Cellular, Ethernet) to LoRaWAN protocol. This parameter change reduces transmission power requirements and simplifies protocol overhead, enabling data transmission with significantly lower power consumption while maintaining adequate communication capability for wildfire detection applications.
Solution Approach 2:
The system replaces the mechanical/electromagnetic communication mechanisms of traditional protocols with a specialized low-power radio frequency protocol (LoRaWAN) optimized for long-range, low-data-rate transmissions. This substitution eliminates the need for high-power transmitters and complex protocol stacks, reducing power consumption while preserving essential data transmission functionality.
3Reliability
If mesh network topology is used for sensor interconnection, then network reliability is improved through redundancy, but power consumption increases as antenna activity is required for multiple connections
Solution Approach 1:
The patent applies periodic action by implementing duty cycling in the mesh network, where sensors transmit data periodically rather than continuously. This allows the network to maintain redundancy and reliability through periodic check-ins and data exchanges, while sensors spend the majority of time in low-power states. The periodic transmission schedule ensures network reliability is maintained without requiring continuous antenna activity for all connections.
4Area of stationary object
If stationary surveillance systems are expanded to increase coverage, then detection coverage is improved, but system cost and installation time increase
Solution Approach 1:
The patent implements universality through the use of LoRaWAN protocol, which provides long-range communication capability that allows a single sensor node to effectively monitor a large area. This multi-functional approach enables one sensor to perform the detection coverage that would traditionally require multiple sensors, reducing installation cost and time while maintaining comprehensive detection coverage.
Solution Approach 2:
The system transitions from a two-dimensional ground-based sensor deployment model to a three-dimensional network utilizing long-range radio frequency communication. This dimensional change allows sensors to communicate over extended distances without requiring physical proximity or complex infrastructure, enabling expanded coverage with fewer, more strategically positioned sensors that are easier and cheaper to install.
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.