Inspiration
This project was built to tackle the challenge presented by Martello to take the data from a murder crime scene and present the information in a way that is meaningful to the authorities conducting the investigation.
What it does
For this challenge we were provided with a JSON file that listed all of the interactions that occurred between the residents of the hotel and the technology inside the hotel in the two days before the murder.
I designed a python script that took the data given in the JSON file and sorted it into the interactions experienced by each of the hotel residents.
How I built it
I used Python to analyze and organize the data and export the information to an excel spreadsheet as a CSV file. The web application, written with HTML and JavaScript, allows the user to upload their JSON data and the back-end server will process the file with the Python script.
Challenges I ran into
We initially tried to analyze the data with Javascript, but we soon found out that Python was a better language choice to deal with the data set which had over 400 data points in it. Once we switched into sorting the data using Python we were able to proceed and tackle more challenging problems.
The most difficult part of this challenge was trying to establish key points in the 2-day storyboard and develop a way to highlight these key data points. In the end we weren't able to solve this problem, however if we were to tackle it again, we think a good way to zone in on key information is to create a proximity heat map that shows when people pass by close to the crime scene.
Accomplishments that I'm proud of
Under a very tight time frame, we were able to produce a working model of our solution for the Martello challenge. This tool can be useful for the forensics team to visualize the interactions of the suspects with respect to the environment in a consolidated and clean manner.
What I learned
I learned how to use Python to manipulate big data and use it in conjunction with JavaScript.
What's next for Murdr Solvr
The next step with the analytics web application is to allow for data visualization using graphs and a floor plan heat map detailing the proximity of the suspects to the victim with relation to time. As well, each interaction will be rated with a score to provide a predictive aspect to the application.
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