12 DISC
Simple Artificial Intelligence Based Prediction Model for Bird Hazard Management System
1. The aim of this software tool is to predict the risk of bird-aircraft collision in real time. The tool will model the spatial- temporal density distributions of key Bird- species in and around the target airfields. It will generate the bird density distributions based on extensive field observations and real time meteorological Conditions along with expert knowledge. The tool will combine the model bird density distributions with historical bird collision data to predict the quantified risk of bird-aircraft collision at any point of time, any day of year at the target airfields of Indian Air Force.
2. The entire project shall consist of following modules:-
(a) Average Bird Density Prediction.
This will be the basic module used in bird density predictions. The generated results will be based on historical data. generally expected seasonal trends under average conditions and expert knowledge of bird behaviour and habitat affecting factors
(b) Real-Time Bird Density Correction: This module will interface with remote sensors to monitor climate and other meteorological conditions. Based on the real time conditions. it will refine and update the predictions from the previous average model for the immediate next 24hrs to 3 days
(c) Bird-Aircraft Collision Hazard Quantification. The level of hazard posed by each individual bird species needs to be quantified. It will be analyzed from the data obtained from Air Force Bird-Strike database. A composite hazard risk will be computed based on the number of strikes. level of associated damage and mass of each individual bird species.
