Infrared Sensor Tracking Human Movement Trajectories
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current systems lack the capability to effectively analyze human movements, trajectories, and activities within environments, such as stores, to optimize operations and understand customer behavior, and they do not provide real-time data on spatial and temporal patterns of traffic and occupancy levels.
Innovation Solution
A system utilizing infrared (IR) energy data from thermopile sensor modules to detect and track human presence, determine location coordinates, and analyze movements, trajectories, and behaviors without requiring personal biometric data, using a network of sensor nodes, a gateway, and a cloud computing module to provide real-time location, trajectory, and behavior analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If basic machines are used to count people entering and exiting a store, then the number of people can be tracked, but detailed information about customer movements, trajectories and activities within the store cannot be obtained
Solution Approach 1:
The patent replaces basic mechanical counting machines with an infrared sensor-based detection system. The system uses IR sensors to detect thermal signatures of customers, automatically tracking their movements, trajectories and activities without requiring complex mechanical counting devices or manual intervention.
Solution Approach 2:
The patent introduces infrared sensors as an intermediary between the customers and the data collection system. These sensors detect thermal radiation from customers and convert it into actionable data about their movements and behaviors, serving as a mediator that captures detailed information without direct contact or complex mechanical interaction.
2Measurement precision
If infrared sensor modules are used to detect and track human presence, then detailed movement and behavior data can be obtained, but the system requires multiple sensor nodes, gateways and cloud computing modules increasing complexity
Solution Approach 1:
The patent divides the detection system into multiple independent sensor nodes, each capable of detecting IR signatures in its local area. These segmented nodes work together to provide comprehensive coverage, with each node handling local detection independently before data is aggregated at higher levels (gateway and cloud).
Solution Approach 2:
The patent adds spatial and temporal dimensions to the tracking system by deploying sensors at multiple locations and collecting data over time. This multi-dimensional approach enables precise trajectory mapping and behavior analysis, transforming simple presence detection into comprehensive movement tracking across space and time.
3Productivity
If the system collects detailed spatial and temporal data on customer movements, then business operations can be optimized, but more energy and computational resources are required for data processing
Solution Approach 1:
The patent implements edge computing capabilities at the sensor node and gateway levels, allowing the system to process and filter data locally before transmitting to the cloud. This self-service approach reduces the computational burden on centralized servers and minimizes energy consumption by performing preliminary analysis at the source.
Solution Approach 2:
The patent applies selective data collection and processing, focusing computational resources on analyzing only the most relevant movement patterns and behaviors. Rather than processing all collected data equally, the system identifies and analyzes key trajectories and activities that provide the greatest business value, reducing overall computational energy requirements.
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
Enables accurate tracking and analysis of human activities, optimizing business operations, improving resource allocation, and providing insights into customer behavior and spatial-temporal patterns, without the need for personal biometric data, while being scalable and adaptable to various environments.
Implementation Method 1
determining location coordinates of the object in the space, based on infrared (IR) energy data of IR energy from the object
Implementation Method 2
determining a temperature of an object in a space, based on infrared (IR) energy data of IR energy from the object
Data Source
AI summary
The system may include a setup app that is configured to locate, track and/or analyze activities of living beings in an environment. The system may be configured for determining a temperature of an object in a space, based on infrared (IR) energy data of IR energy from the object, determining location coordinates of the object in the space, comparing the location coordinates of the object to location coordinates of a fixture and determining that the object is a human being, in response to the temperature of the object being within a range, and in response to the location coordinates of the object being distinct from the location coordinates of the fixture.