IoT Sensor Network Validation via Real-Time Signal Measurement
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Solution Overview
Problem
Current methods for deploying IoT sensors lack accuracy in determining optimal locations for predictable connectivity, leading to high operational costs and truck rolls due to statistical modeling variabilities and differences in RF characteristics among low-cost IoT modules.
Innovation Solution
A system comprising an API/mobile platform, hardware kit/dongle, communication network, server, and network modules that measures signal strength in real-time to determine optimal IoT sensor deployment locations based on network intelligence, using a cloud-based Geographic Information System (GIS) and analytics engine for data processing and visualization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If statistical modeling using terrain and clutter models is used for sensor deployment, then deployment coverage can be estimated, but measurement precision and reliability of connectivity prediction deteriorate due to statistical variabilities
Solution Approach 1:
The patent uses actual IoT sensor devices to copy and replicate real-world measurement conditions. Instead of relying on statistical models, the system deploys multiple identical or similar IoT sensors at candidate locations to directly measure and report actual signal strength, replacing theoretical modeling with empirical data collection from representative devices
Solution Approach 2:
The system implements feedback loops where IoT sensors continuously measure and report actual signal strength to a server. The server processes this feedback data to identify optimal locations, then validates predictions by having sensors at those locations perform measurements. This closed-loop feedback mechanism enables continuous refinement of location recommendations based on actual measured performance rather than statistical estimates
2Ease of manufacture
If low cost IoT modules are used to reduce device cost, then manufacturing cost decreases, but measurement precision deteriorates due to differences in RF characteristics among modules
Solution Approach 1:
Each low-cost IoT module performs its own self-measurement of signal strength at its deployment location and automatically reports results to the server. The system leverages the inherent capabilities of each individual module to measure its own operating conditions, eliminating the need for centralized calibration or high-precision reference equipment. This self-service approach allows heterogeneous low-cost modules to contribute valid measurement data despite manufacturing variations
Solution Approach 2:
The system changes the measurement parameter from requiring absolute precision to measuring relative signal strength thresholds. Instead of demanding highly precise and consistent RF characteristics across all modules, the system determines optimal locations based on whether signal strength exceeds minimum thresholds for reliable connectivity. This parameter transformation allows use of low-cost modules with varying RF characteristics while still achieving accurate location optimization
3Measurement precision
If traditional RF scanning tools are used for network measurement, then measurement capability is available, but device complexity and cost increase due to bulky equipment requirements
Solution Approach 1:
The patent replaces complex professional RF scanning equipment with copies of actual IoT sensor devices. These simplified devices replicate the essential measurement function by using the same network modules and antennas that will be deployed in production. This copying approach eliminates the need for bulky, expensive measurement tools while maintaining measurement relevance to actual operational conditions
Solution Approach 2:
The IoT devices themselves perform the measurement function they were originally designed for - communicating with the network. By leveraging their built-in network capabilities, the devices automatically measure signal strength as a byproduct of their normal operation. This self-service measurement eliminates the need for separate, complex measurement equipment while using the devices' inherent communication capabilities
Data Source
AI summary
The invention relates cloud based IoT network monitoring and validation to enable optimal network selection and connectivity for IoT sensors. The present invention relates to a system to measure the signal quality directly from the network module of IoT sensors. It comprises of an application programming interface (API) 105, a Network detection dongle 103, communication network 110, server 115, network modules of network operators and IoT sensors 120, to be deployed or installed. The invention also relates to a method for determination of signal strength from network module of IoT sensors, wherein the API 105 is configured to run network detection software to determine and validate an optimal location for IoT sensor/device installation or deployment based on the highest signal strength.