Sensor Node Positioning via Coverage Distribution Minimization
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Solution Overview
Problem
Sensor placement in sensor networks is complex due to the need for maximum coverage with a minimum number of sensors, especially in dynamic and heterogeneous environments, where sensor performance and environmental constraints complicate the determination of optimal sensor positions over time.
Innovation Solution
A method for determining sensor node positions based on a defined coverage distribution and prior probability distribution, using minimization of distance between these distributions, with embodiments including initial deployment, trajectory computation, and periodic updates, especially for autonomous vehicles with local controllers and global state vector consensus.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If the number of sensors is increased to achieve maximum coverage, then the coverage area is improved, but the system complexity and placement decision complexity increase
Solution Approach 1:
The patent replaces manual or mechanical sensor placement methods with an automated optimization algorithm that computes optimal sensor positions based on coverage requirements. The system uses mathematical optimization to automatically determine placement decisions, eliminating the need for complex manual placement planning while achieving maximum coverage with minimum sensors.
2Productivity
If sensor placement is optimized for maximum coverage, then the coverage efficiency is improved, but the computational complexity for determining optimal positions increases
Solution Approach 1:
The patent segments the sensor network into multiple zones or regions, and optimizes sensor placement for each zone independently or semi-independently. This segmentation reduces the overall computational complexity by breaking down the large-scale optimization problem into smaller, more manageable sub-problems while still achieving global coverage efficiency.
Solution Approach 2:
The optimization algorithm considers local environmental characteristics and constraints when determining sensor placement in different regions. By adapting placement strategies to local conditions rather than applying a uniform approach, the system achieves high coverage efficiency while reducing computational burden through localized optimization.
3Adaptability or versatility
If heterogeneous sensors are used to meet diverse sensing requirements, then the sensing capability is improved, but the placement decision complexity increases
Solution Approach 1:
The patent employs a unified optimization framework that can handle multiple sensor types and sensing requirements within a single placement decision system. The algorithm automatically determines the optimal placement for different heterogeneous sensors based on their specific functions and coverage characteristics, eliminating the need for separate placement decisions for each sensor type while maintaining diverse sensing capabilities.
Data Source
AI summary
A method of sensor node position determination for a sensor network is provided. A coverage distribution is defined based on a number of sensor nodes and sensor footprints of the sensor nodes. A desired position for each of the sensor nodes is determined based on the coverage distribution and a prior probability distribution defined on a bounded domain for the number of sensor nodes as a minimization of a distance between the coverage distribution and the prior probability distribution. The desired position to configure the sensor nodes is output.