Sensor-Based Resource Consumption Tracking for Bulk Storage Racks
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Large complexes, such as distribution hubs, face inefficiencies in tracking and tabulating service resource consumption, leading to wasteful over-ordering due to a lack of data on availability and consumption, necessitating a system for automatic tabulation and tracking.
Innovation Solution
A resource consumption system that includes sensors to detect resource delivery and consumption events, transmitting notifications to a computing environment for processing and generating requests for imbursement, with a dashboard for real-time tracking and predictive analysis to optimize resource management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual tracking of service resources is used in large complexes, then device complexity is reduced, but measurement precision and information availability deteriorate, leading to wasteful over-ordering
Solution Approach 1:
The system employs self-service mechanisms where sensors automatically detect resource consumption events and the computing environment autonomously processes this data to generate imbursement requests. The dashboard automatically tracks and reports consumption without manual intervention, enabling the system to serve itself in monitoring and reporting resource usage, thereby achieving high measurement precision without proportionally increasing operational complexity
Solution Approach 2:
The patent replaces manual mechanical tracking methods with automated sensing and computing systems. Sensors detect resource consumption events and transmit data to a computing environment that processes information and generates requests automatically. This substitution of mechanical/manual processes with electronic sensing and computational systems achieves precise measurement while managing system complexity through automation
2Quantity of substance
If bulk container organization of service resources is used, then storage efficiency is improved, but measurement precision and consumption tracking deteriorate
Solution Approach 1:
The system segments the bulk container resources into trackable units by using sensors that detect individual consumption events. Each resource unit within the bulk container is monitored independently through sensor detection, allowing the system to track consumption at the unit level even while resources are stored in bulk containers. This segmentation enables precise measurement of individual resource usage while maintaining bulk storage efficiency
Solution Approach 2:
The system implements feedback mechanisms where sensors continuously monitor resource consumption events and transmit data to the computing environment. This real-time feedback loop provides accurate information about unit-by-unit consumption from bulk containers, enabling the system to maintain both bulk storage efficiency and precise consumption tracking through continuous monitoring and data processing
3Loss of information
If automatic sensor-based tracking is implemented, then measurement precision and information availability improve, but device complexity and initial cost increase
Solution Approach 1:
The computing environment serves multiple functions: it receives sensor data, processes consumption information, generates imbursement requests, and provides dashboard reporting. This multi-functional approach consolidates what could be separate complex systems into a single universal platform, reducing overall system complexity while maintaining comprehensive information availability and measurement precision
Solution Approach 2:
The patent merges the sensing, data processing, request generation, and reporting functions into an integrated system. The computing environment combines multiple capabilities that could operate as separate systems, and the dashboard integrates real-time tracking with historical analysis and predictive features. This merging reduces the number of separate components and interfaces, managing device complexity while achieving comprehensive information availability
4Productivity
If real-time dashboard tracking is implemented, then productivity and decision-making speed improve, but use of energy and computational resources increase
Solution Approach 1:
The dashboard implements periodic updates and reporting cycles rather than continuous real-time processing. Sensors transmit consumption event data at discrete intervals, and the computing environment processes information in batches during scheduled cycles. This periodic action maintains productivity by providing timely updates while reducing energy consumption compared to continuous real-time processing of all data streams
Data Source
AI summary
A resource consumption system can include a plurality of resources positioned within at least one rack and at least one sensor configured to detect removal of an amount of the plurality of resources from the respective rack. The resource consumption system can include at least one transmitter configured to transmit a notification based on the at least one sensor detecting the removal of the amount of resources, wherein the notification comprises a resource identifier, an entity identifier, and the amount of the plurality of resources. The resource consumption system can include at least one computing device configured to compute an amount based on the resource identifier and the amount of resources, generate a request based on the notification, and transmit the request to an entity associated with the entity identifier, wherein the request comprises the resource identifier, the entity identifier, and the amount.