The system is directed to support emergency services. It will predict the type and probability of emergencies that may occur in a certain area in a defined interval of time throughout the day. Analyzing emergency response data set and discovering hidden trends and patterns will help in ensuring that the emergency response team is better equipped to deal with emergencies. Considering road accidents, fire accidents and other medical emergencies etc.,
high numbers in specific areas indicate that there is a high demand for ambulance or other emergency services in those areas. Road accidents in some areas might be due to road conditions which need to be improved. High frequency of emergencies due to respiratory problems might be due to harmful pollutants in the air in that specific area.
using Association rule mining using apriori algorithm will thus help in discovering such patterns.
1.4 Proposed System
The proposed system consists of pre processing the data set, applying association rule mining, extracting interesting patter from the rules obtained and lastly validation of rules. The dataset contains post emergency record of City. The attributes include: type of emergency, type of response, quantity of response elements, time stamp, and area where the emergency has occurred. To start with, the system will analyze the current data which was recorded so far by Rescue Organization and will create rules according to that data. The same data will be used to create rules and carry out machine learning. Later, as an iterative process, the real-time data will help to continue machine learning process. Progressively, some old rules will be deleted or altered and new rules will be formed by machine under automation. Therefore, the probabilities produced by the system will also be affected as the physical environment variables change the data which in turn change the rules. The rules will be defined on the basis of real-time data as well as scientific research in medical field encompassing human body response to its physical environment such as pollution, stress, or eating disorders. The system will automate the human decision making process which is presently completely manual or intuition based. It will streamline the daily processing of employees at headquarters of Rescue
Using Machine Learning to Predict Car Accident Risk. The data will be on excel file (day,time,vehicle,sex,weather etc. about 50-70 conditions). The program must compare several models and as a result to export on map and on plots prediction risk analysis about car accidents and area where the accidents, conclusions. I also need a fully detailed documentation of the project 15000 - 20000 words and bibliography.
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