Modular Edge Weather Monitoring With AI for Sparse Station Coverage
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Solution Overview
Problem
Existing weather reporting and prediction systems lack the accuracy and coverage needed to improve public safety, particularly in areas prone to severe weather events, due to the scarcity of edge computing and AI capabilities in weather stations, with only 2000 FAA-approved stations in the US, resulting in inadequate monitoring of weather conditions across vast areas.
Innovation Solution
A modular edge intelligence platform that includes a base station for communication and an application module for specific functionalities, such as weather analysis, deployed atop streetlights, equipped with AI capabilities to process cloud formation images and transmit data via low-bandwidth wireless communication, enabling detailed weather monitoring and prediction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional weather stations are deployed, then weather monitoring capability is provided, but the coverage area is limited and measurement precision is insufficient due to scarcity of stations
Solution Approach 1:
The patent segments the monolithic weather station system into modular components: a base station providing communication functionality and separate application modules (such as weather modules) that can be selectively attached. This modularization enables deployment of numerous low-cost monitoring units across wide areas, transforming the system from sparse centralized stations to distributed edge intelligence nodes, thereby improving coverage and measurement precision without requiring fewer stations
Solution Approach 2:
The weather module integrates edge computing capabilities and AI processing directly at the monitoring point, enabling the system to perform local weather analysis and prediction without continuous cloud connectivity. This self-service approach allows each distributed station to independently provide accurate local weather monitoring, significantly expanding coverage area while maintaining high measurement precision through localized intelligent processing
2Measurement precision
If edge computing and AI capabilities are added to weather stations, then weather analysis accuracy is improved, but device complexity and installation cost increase
Solution Approach 1:
The patent divides the complex weather monitoring system into a simple base station and separate functional application modules. The base station provides basic communication functionality, while the weather module (containing edge computing and AI capabilities) is a self-contained unit that attaches to the base station. This segmentation isolates complexity within the modular weather module, keeping the base station simple and reducing overall system complexity through standardized interfaces
Solution Approach 2:
The base station is designed as a universal platform that can support multiple different application modules (weather monitoring, security, environmental sensing, etc.). This multi-functionality allows the same base infrastructure to serve various purposes, reducing device complexity by eliminating the need for separate dedicated stations for each function while maintaining high analysis accuracy through specialized modular add-ons
3Productivity
If modular edge computing platform is deployed on streetlights, then deployment speed and coverage are improved, but ease of manufacture may be affected
Solution Approach 1:
The patent segments the edge computing platform into a standardized base station unit and separate application modules, where the base station contains communication and power management functionality. This segmentation allows for specialized manufacturing of each module independently using optimized processes, then assembly through standardized mechanical and electrical interfaces, thereby maintaining manufacturing simplicity while enabling rapid deployment of complete systems
Solution Approach 2:
The modular design allows different application modules to be attached to the same base station depending on deployment needs. This parameter change capability means the core base station can be manufactured once with standardized parameters, while only the smaller, simpler application modules need customization for different functions (weather, security, traffic), significantly simplifying the overall manufacturing process while maintaining high deployment productivity
Data Source
AI summary
A system for sensing and responding to detected activity or an event in a region is provided. The system may comprise: a modular edge computing platform configured to provide a predetermined functionality for a particular application, the modular edge computing platform is configured to process sensor data to generate processed data, and transmit the processed data; and a remote entity that comprises (i) a cloud analytic configured to receive the processed data from the modular edge computing platform and analyze the processed data, and (ii) a cloud user interface module configured to provide a graphical user interface on a user device, the graphical user interface displays one or more results generated by the cloud analytic upon analyzing the processed data.