Dynamic Entity Tracking System Using RFID and GPS Sensors
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current tracking systems in dealership and warehouse environments are inefficient, relying on manual methods and paper-based systems, which increase the likelihood of movable entities being misplaced and lead to higher operational costs, and lack dynamic tracking capabilities to simulate and analyze operations effectively.
Innovation Solution
A system and method that uses electronic tracking devices with RFID or GPS technology to dynamically track entities, sensing signals from tags, processing location data, and updating paths on a displayed map, allowing for real-time monitoring and forecasting of operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If manual tracking methods (bar-coded labels, magnetic stripe tags, paper documents) are used, then device complexity is reduced, but tracking reliability and measurement precision deteriorate
Solution Approach 1:
The patent replaces manual tracking methods (mechanical/paper-based systems) with electronic tracking devices using RFID or GPS technology. These electronic systems automatically detect and record entity locations without human intervention, significantly improving tracking reliability while maintaining acceptable system complexity through standardized hardware components.
Solution Approach 2:
The tracking system enables entities to be tracked autonomously through self-contained electronic tags that automatically transmit location data. The system serves itself by continuously monitoring and updating entity positions without requiring manual scanning or paper documentation, thereby improving reliability without proportionally increasing complexity.
2Measurement precision
If continuous electronic tracking is implemented, then tracking reliability and measurement precision improve, but use of energy and device complexity increase
Solution Approach 1:
The system implements periodic tracking updates rather than truly continuous monitoring. Electronic tags transmit location data at predetermined time intervals or when triggered by specific events, maintaining measurement precision for entity locations while significantly reducing energy consumption compared to constant transmission modes.
Solution Approach 2:
The tracking system dynamically adjusts its operation mode based on entity movement and operational context. Tracking intensity and update frequency are optimized according to actual needs, allowing the system to maintain measurement precision when required while conserving energy during stable states, thus balancing precision and energy consumption.
3Reliability
If RFID/GPS electronic tracking devices are used, then tracking reliability improves, but device complexity and manufacturing cost increase
Solution Approach 1:
The patent employs universal electronic tracking devices (RFID tags or GPS receivers) that can track multiple types of entities (vehicles, containers, equipment) through a single standardized system. This multi-functionality approach improves tracking reliability across diverse applications while avoiding the need for specialized complex devices for each entity type, thereby controlling overall device complexity.
4Productivity
If dynamic tracking and forecasting capabilities are added, then productivity and operational efficiency improve, but device complexity and loss of time for data processing increase
Solution Approach 1:
The system incorporates feedback mechanisms where tracking data is continuously collected, processed, and used to generate real-time forecasts of entity locations and operational status. This feedback loop enables dynamic adjustments and predictive analytics that improve productivity while the automated nature of the feedback processing minimizes additional complexity compared to manual analysis methods.
Solution Approach 2:
The forecasting capability performs preliminary analysis of tracking data to predict future entity locations and potential operational issues before they occur. By proactively identifying trends and potential problems, the system enables preventive actions that improve productivity while the automated forecasting algorithms manage data processing complexity efficiently.
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 continuous, accurate tracking of movable entities, reducing the risk of misplacement and improving operational efficiency by providing real-time data for productivity enhancements and dynamic simulation of operations.
Implementation Method 1
These tags may use either radio frequency identification (RFID) or global positioning system (GPS) technologies. Applications of RFID technology are wide ranging and involve detection of tagged entities as they pass or are stationed near a RFID sensor or reader via unique identification of specific tags associated with these entities
Implementation Method 2
Applications of GPS technology involve determining a position of a GPS receiver or entity by measuring the distance between itself and three or more GPS satellites. Measuring the time delay between transmission and reception of each GPS radio signal gives the distance to each GPS satellite, since the signal travels at a known speed
Data Source
AI summary
A method is provided for dynamically tracking a plurality of entities progressing through an operation each having an electronic tagging device associated therewith. The method includes sensing signals emitted by each of the plurality of tagging devices, at predetermined instances or when triggered by external events, by a plurality of sensors located at predetermined sites with respect to the operation, each signal including information uniquely identifying the corresponding tagging device, communicating the sensed signals and corresponding energy levels at which they were sensed by each of the plurality of sensors to a data processor, processing the unique identification information provided by the signals and their energy levels to determine a location of each tagging device relatively to the predetermined sites of the sensors, and dynamically updating a path of each tagging device and the associated entity based on the determined location with respect to at least a portion of a displayed map of the operation.