Meat Weight Estimation System for Hunter-Processor Ordering
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Solution Overview
Problem
Hunters face difficulties in finding and selecting a quality processor to butcher their animals efficiently, as they often lack information about available services and costs, and struggle with the process of ordering specific cuts of meat without knowing the animal's weight.
Innovation Solution
A system comprising a database for estimating meat weight based on animal characteristics, a server, and a mobile application that allows users to select a processor, input animal characteristics, allocate meat weight to desired products, and generate an order, which is then sent to the processor for processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If hunters manually deliver animals to processors without digital tools, then the process is simple and requires minimal technology, but it causes time loss and lacks information about processor services and costs
Solution Approach 1:
The patent introduces a mobile application as an intermediary between hunters and processors. The app provides a user-friendly interface that displays processor information, service options, and cost estimates, eliminating the information gap without requiring complex backend systems. The server acts as a mediator that processes animal characteristics and returns estimated meat weights, simplifying the overall system architecture.
Solution Approach 2:
The system creates a digital copy of the meat weight estimation process by using database tables to store and retrieve weight data based on animal characteristics. This allows the system to provide accurate estimates without requiring physical measurement equipment at each interaction point, simplifying the overall system while maintaining precision.
2Loss of time
If hunters don't know the animal's meat weight before ordering, then the ordering process is simple, but it causes time loss and inability to plan purchases
Solution Approach 1:
The system performs preliminary action by estimating the meat weight before the actual ordering process. The server calculates the estimated meat weight based on animal characteristics (species, weight, age, gender) and provides this information to the hunter before they place their order. This allows hunters to plan their purchases in advance and understand what they can expect to receive.
Solution Approach 2:
The system implements feedback by providing real-time weight estimates to the hunter after inputting animal characteristics. The estimated meat weight is displayed to the hunter, allowing them to adjust their ordering preferences and understand the potential cost before finalizing their purchase plan.
3Manufacturing precision
If hunters manually specify cut preferences without weight knowledge, then the ordering interface is simple, but it results in inaccurate orders and processing errors
Solution Approach 1:
The ordering interface is made dynamic by automatically adjusting cut preferences and quantities based on the estimated meat weight. As the system processes animal characteristics and generates weight estimates, the interface dynamically updates available ordering options, allowing hunters to select cuts that match their actual meat supply rather than making generic selections.
Solution Approach 2:
The system performs self-service by automatically calculating weight estimates and generating order recommendations based on the hunter's input. The server processes the animal characteristics, retrieves relevant data from databases, and presents tailored ordering options without requiring manual calculation or complex user input, simplifying the interface while improving accuracy.
4Productivity
If processors receive vague order information, then the processing workflow is simple, but it causes time loss and requires additional verification
Solution Approach 1:
The system performs preliminary action by pre-calculating and providing detailed order information to the processor before the actual processing begins. The server generates comprehensive order data including estimated meat weight, selected cuts, and associated costs, which is transmitted to the processor in advance. This allows processors to prepare their workflows and verification processes ahead of time.
Solution Approach 2:
The system implements feedback by providing detailed order confirmations and weight estimates to both hunters and processors. The server sends back processed information about the order, including confirmed weights and cut allocations, allowing processors to verify orders quickly and accurately without requiring additional communication or verification steps.
Data Source
AI summary
Method and apparatus are disclosed for processing meat. An example system comprises a database that includes estimates of meat weight associated with characteristics of an animal. The system also includes a server that, after receiving first characteristics of a first animal, generates a first meat weight of the first animal using the estimates in the database. Additionally, in some examples, the system includes an application that is downloadable onto a mobile device. The application (i) receives, via a first presented interface, a selection of the first animal, (ii) receives, via a series of second presented interfaces, the first characteristics of the first animal, (iii) sends the first characteristics to the server and receives the first meat weight, (iv) receives, via a series of third presented interfaces, an allocation of the first meat weight to goods offered by a processor, and (v) composes an order based on the allocation.