Species Pattern Evaluation Using Predictive Feeding
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Solution Overview
Problem
Current methods for evaluating species patterns in wildlife habitats lack effectiveness in predicting species presence over time, particularly in wildlife conservation, hunting, and animal watching, as they do not provide reliable predictive estimates of species probability during future time periods.
Innovation Solution
A system utilizing multiple cameras and a weather station to monitor animal activity areas, with cameras positioned to capture animal paths and recognize species, and a feeder with wireless communication capabilities to selectively feed target species while deterring others, using data analysis and predictive algorithms to estimate species presence based on historical data and environmental factors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional species pattern evaluation methods are used, then implementation is simple, but predictive accuracy of species presence is insufficient
Solution Approach 1:
The system segments species pattern evaluation into multiple independent components: camera-based species identification, weather station environmental monitoring, feeder behavior tracking, and predictive algorithm processing. Each component collects and analyzes specific data types independently, then integrates results to achieve high predictive accuracy without overwhelming system complexity.
Solution Approach 2:
The patent introduces a predictive algorithm as an intermediary that processes raw data from cameras, weather stations, and feeders. This intermediary layer transforms disparate data sources into meaningful species presence predictions, resolving the contradiction by providing accurate predictions through a structured intermediate processing stage rather than direct observation.
2Reliability
If multiple cameras and weather stations are deployed to monitor animal activity, then species presence prediction improves, but device complexity and cost increase
Solution Approach 1:
The camera system is designed to perform multiple functions: species identification, individual animal recognition, behavior monitoring, and data collection for predictive algorithms. This multi-functionality allows a single camera deployment to support various monitoring needs simultaneously, improving prediction reliability without proportionally increasing system complexity.
Solution Approach 2:
The system implements feedback loops where camera and weather station data continuously update predictive models, which in turn guide camera positioning and monitoring priorities. This feedback mechanism improves prediction reliability by iteratively refining models based on actual observations, while the automated feedback process prevents manual intervention complexity.
3Productivity
If selective feeding of target species is implemented, then wildlife management effectiveness improves, but system complexity increases
Solution Approach 1:
The feeder system applies local quality by providing different feeding conditions to different species at the same location. Target species receive appropriate feed through unlocked mechanisms, while non-target species are deterred by electrical shocks or remain unaffected. This localized differentiation achieves effective wildlife management without requiring entirely separate feeding systems for each species.
Solution Approach 2:
The system changes operational parameters of the feeder based on detected species: electrical shock activation, lock mechanism engagement, and feed dispensing are all controlled by changing system parameters in response to camera identification. This parameter-based control achieves selective feeding through automated parameter adjustment rather than mechanical complexity.
Data Source
AI summary
Methods of evaluating animal activity relating to wildlife areas are disclosed that include running a digital classification routine to recognize particular species in a series of images. From those images data records are developed having the ability to identify timing information, the species, the location, celestial characteristics and atmospheric characteristics. The data records are analyzed to establish correlations between various associated features and the presence of the particular species. Data associated with future celestial characteristics and atmospheric characteristics is obtained and estimated probabilities of future appearances of the particular species are calculated and provided.