Location Analytics Server Visitor Classification
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing location analytics solutions rely on fixed, universal criteria for classifying wireless devices as visitors or passersby, leading to inaccurate results due to variations in signal strength and detection patterns across different locations and device types, and fail to account for the presence of visitors without detectable wireless devices.
Innovation Solution
A location-specific configuration system that classifies wireless devices based on criteria such as minimum signal strength, number of detections, and device type, using multiple sensing devices with overlapping reception areas to improve accuracy, and estimates actual visitor numbers by applying location-specific factors derived from on-site measurements or demographic data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If fixed universal criteria are used for classifying wireless devices as visitors or passersby, then the system is simple to implement, but the classification accuracy deteriorates due to variations in signal strength and detection patterns across different locations and device types
Solution Approach 1:
The patent implements location-specific configurations that define custom criteria for each observed location, including location-specific minimum signal strength thresholds, detection number requirements, and time interval settings. This allows the system to adapt to local characteristics such as building materials, antenna placements, and environmental factors that affect wireless signal propagation differently at each location, thereby improving classification accuracy without requiring a completely complex system overhaul.
Solution Approach 2:
The system dynamically adjusts classification criteria based on device type information. Different wireless device types (smartphones, tablets, laptops, IoT devices) have different detection patterns and signal characteristics. The patent enables the system to apply different criteria sets depending on the detected device type, making the classification process adaptive and dynamic rather than static, which improves accuracy while maintaining manageable complexity through automated device type recognition.
2Measurement precision
If location-specific configurations with multiple criteria are implemented, then the classification accuracy improves, but the complexity of configuring and managing the system increases
Solution Approach 1:
The patent implements automated calibration procedures that perform preliminary actions to establish location-specific criteria. The system automatically collects signal strength data and detection patterns during initial operation at each location, then uses this data to configure appropriate minimum signal strength thresholds, detection numbers, and time intervals. This preliminary automated configuration reduces the manual setup burden and makes the system easier to deploy at new locations while maintaining high classification accuracy.
Solution Approach 2:
The system incorporates self-optimization capabilities where the location analytics server automatically adjusts and refines classification criteria based on accumulated data from wireless sensing devices. The system monitors classification results and signal patterns over time, then autonomously tweaks parameters like minimum signal strength thresholds and detection time intervals to optimize performance at each specific location, reducing the need for manual reconfiguration and expert intervention.
3Measurement precision
If multiple wireless sensing devices with overlapping reception areas are deployed, then the measurement precision of visitor classification improves, but the device complexity and cost increase
Solution Approach 1:
The patent divides the observation area into multiple zones, each monitored by specific wireless sensing devices with defined reception areas. By segmenting the space and assigning devices to specific zones, the system achieves more reliable detection through overlapping coverage without requiring excessive devices throughout the entire area. The location analytics server correlates data from multiple devices to classify visitors, making the segmentation efficient and cost-effective.
4Measurement precision
If location-specific factors derived from on-site measurements are applied, then the estimation of actual visitor numbers improves, but the time and resources required for setup increase
Solution Approach 1:
The patent performs automated calibration during initial system setup that collects signal strength data and detection patterns at the observed location, then uses this data to determine location-specific factors such as average signal strength levels, detection probabilities, and conversion factors between detected devices and actual visitors. This preliminary automated data collection and factor determination reduces manual measurement time and resources while improving the accuracy of visitor number estimates.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach provides more accurate real-time classification and estimation of visitor numbers, enabling effective automation of facility systems such as air conditioning, lighting, and guidance, by accounting for location-specific characteristics and device variations.
Implementation Method 1
If, for example, a wireless device is seen for more than five minutes with a Received Signal Strength Indication (RSSI) of 10 or more, the location analytics server may determine that the wireless device belongs to a visitor.
Data Source
Figure 1
Figure 2
Figure 3a~3b
AI summary
The present disclosure relates to a system (100) comprising a location analytics server (108) and one or more wireless sensing devices (104) installed at a location (102) to be observed. Each of the one or more wireless sensing devices (104) is configured to transmit information about detected wireless devices (112) to the location analytics server (108) and the location analytics server (108) is configured to analyze the information about the detected wireless devices (112) to classify, for each of the detected wireless devices (112), whether the respective wireless device (112) is a visitor device or a passerby device, wherein classifying the respective wireless device (112) is performed based on a location-specific configuration comprising at least one criterion to be satisfied for classifying the respective wireless device (112) as a visitor device, wherein the at least one criterion is specifically adapted to the location (102).