Low-Energy IoT Tags for Passive Stock Item Detection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current solutions for monitoring and managing inventory, particularly for small-size objects, are inefficient and prone to errors due to reliance on manual labor, complex infrastructure, or ineffective technologies like RFID and bar code systems.
Innovation Solution
The implementation of a method using low-energy internet of things (IoT) tags that passively detect items and determine their placement points through machine learning algorithms, with a portable gateway device providing energy and communication support.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If RFID tags are used for item tracking, then automated monitoring is enabled, but monitoring fails when tags do not transmit signals or signals are not received, particularly in densely populated areas
Solution Approach 1:
The patent introduces an intermediary device (gateway or reader) that actively queries IoT tags and receives their responses. This intermediary acts as a mediator between the tags and the monitoring system, ensuring reliable data collection even in densely populated areas where direct tag-to-reader communication might fail. The gateway manages the querying process and handles signal reception, improving overall system reliability.
Solution Approach 2:
The system implements feedback mechanisms where the gateway sends queries to IoT tags and receives responses. This bidirectional communication allows the system to verify tag status, receive item information, and maintain reliable monitoring. The feedback loop ensures that even if some tags fail to transmit, the system can identify and compensate for these failures through repeated queries and alternative tag detection.
2Ease of manufacture
If manual labor is used for item placement, then item positioning can be performed, but it is time-consuming and prone to human errors
Solution Approach 1:
The system enables self-service automation where IoT tags attached to items automatically provide their identification information when queried by the gateway. The system autonomously determines placement locations based on item type and guides workers or robotic systems to the correct shelves. This eliminates the need for manual directory searching and reduces placement time significantly while minimizing human errors.
Solution Approach 2:
The system performs preliminary actions by pre-determining placement locations for items based on their identification data. Before physical placement occurs, the system calculates and communicates the optimal shelf location, allowing workers to prepare in advance or robotic systems to navigate directly to the correct position. This preliminary determination of placement points streamlines the entire stocking process.
3Extent of automation
If tracking cameras are used for item monitoring, then automated detection is achieved, but line of sight is required and installation and maintenance are cumbersome
Solution Approach 1:
The patent replaces the mechanical/optical camera-based tracking system with a wireless electromagnetic field-based IoT tag system. Instead of using cameras that require line of sight and complex mounting infrastructure, the system uses small IoT tags that communicate wirelessly with portable gateways. This substitution eliminates the need for physical installation of cameras and complex line-of-sight positioning, significantly reducing device complexity while maintaining automated detection capabilities.
4Extent of automation
If bar code scanning is used for item identification, then automated scanning is provided, but active participation of a person is required resulting in delays
Solution Approach 1:
The IoT tag system enables self-service identification where tags automatically respond to gateway queries without requiring human intervention to present or scan the tag. The tag continuously holds its identification data ready, and the gateway can query it at any time, eliminating the sequential scanning process required by bar code systems. This reduces identification time significantly while maintaining automated scanning capabilities.
Data Source
AI summary
A system and method for passively determining and placing a stock item using an internet of things (IoT) tag is presented. The method includes receiving, during a predefined time window, data packets from a gateway, wherein the received data packets include at least a sensing signal from a plurality of IoT tags; identifying a first IoT tag from the plurality of IoT tags having a signal strength indicator above a predetermined threshold rank, wherein the first IoT tag is attached to a stock item; identifying the stock item, using a machine learning algorithm on the received data packets of the identified first IoT tag; and causing determination of a placement point to place the identified stock item.