Wireless Signal Map Refinement Using Software Sensors
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Solution Overview
Problem
Existing methods for creating and updating wireless signal quality indicator maps in dynamic industrial environments are costly, inefficient, and often require human intervention, leading to irregular measurements and low data quality.
Innovation Solution
A progressive refinement method for wireless signal quality indicator maps that deploys software sensors on existing appliances only when needed, using an app store unit to download sensor applications, and refines the maps based on measured parameters, reducing the need for expensive special-purpose sensors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If dedicated measurement equipment and human operators are used for radio map measurements, then measurement accuracy can be maintained, but the cost increases and automation is lacking
Solution Approach 1:
The patent creates virtual copies of measurement capabilities by deploying software sensors on existing appliances. Instead of using physical dedicated measurement equipment, the system installs software applications that replicate the measurement functionality of expensive hardware on ordinary devices like smartphones and tablets, thereby maintaining measurement accuracy while dramatically reducing deployment costs.
Solution Approach 2:
The patent makes existing appliances serve multiple functions - they continue their primary uses while simultaneously functioning as measurement devices through installed sensor applications. This multi-functionality eliminates the need for dedicated measurement equipment, reducing costs while maintaining measurement capabilities through the universal use of common appliances.
2Productivity
If measurements are performed manually by human operators, then some measurement capability is achieved, but the measurements are irregular and not timely when incidents occur
Solution Approach 1:
The patent transforms the static, manual measurement process into a dynamic automated system. Software sensors continuously monitor radio map parameters and can automatically increase measurement frequency when incidents or anomalies are detected, ensuring timely responses while maintaining regular monitoring operations, thereby eliminating the irregularity inherent in manual measurement schedules.
Solution Approach 2:
The system implements continuous feedback loops where measurement data is automatically analyzed and used to trigger additional measurements or alerts when quality thresholds are not met. This feedback mechanism ensures timely detection of incidents and maintains high measurement frequency without requiring manual intervention, directly addressing the responsiveness issues of manual measurement approaches.
3Area of stationary object
If a large number of static sensors are deployed to cover the area, then measurement coverage improves, but the cost increases due to lack of automation
Solution Approach 1:
The patent enables existing appliances throughout the area to serve as measurement nodes, creating comprehensive coverage without deploying additional dedicated infrastructure. By utilizing devices that already exist in the environment for their primary purposes plus measurement functions, the system achieves wide area coverage while avoiding the costs associated with deploying and maintaining large numbers of specialized sensors.
Solution Approach 2:
The system leverages the existing infrastructure of appliances already present in the measurement area. These devices serve themselves by performing both their primary functions and radio map measurements simultaneously, eliminating the need for separate dedicated measurement infrastructure and reducing overall deployment costs while maintaining comprehensive coverage.
4Measurement precision
If measurements are taken over longer periods of time to improve data quality, then more data points are obtained, but the irregularity of measurements and low number of data points remains a challenge
Solution Approach 1:
The patent implements dynamic measurement scheduling where the frequency and intensity of measurements automatically adjust based on detected conditions. During normal operation, measurements occur at standard intervals, but when anomalies or quality issues are detected, the system automatically increases measurement frequency to gather sufficient data points for ML algorithms, thereby maintaining data quality without requiring excessively long measurement periods.
Solution Approach 2:
The system continuously monitors measurement data quality and uses feedback to trigger additional measurements when data points are insufficient or quality thresholds are not met. This automated feedback mechanism ensures that adequate data is collected for machine learning algorithms without manual intervention, maintaining both data quality and sufficient quantity of data points through adaptive measurement scheduling.
Data Source
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AI summary
The invention discloses an automated method for a progressive refinement of a wireless signal quality indicator map ((4) based on at least one parameter indicating the signal quality of the wireless signal, comprising the steps of: - determining the wireless signal quality indicator map (4) based on measurement by at least one stationary first computerized wireless parameter measuring device (3.1), - determining an area of interest (6) in the wireless signal quality indicator map (4) where the parameter is lower than a pre-defined threshold value and/or the confidence in a measurement value of the parameter is lower than a pre- defined target value, - downloading at least one software-based sensor application (7.2) from an app store unit to at least one stationary computerized appliance (7) located in the area of interest (6), whereby the sensor application (7.2) is dedicated to measure the parameter using hardware and/or software of the appliance (7), and - refining the wireless signal quality indicator map (5) by the parameter measured by the sensor application (7.2). A system related to the automated method is disclosed as well.