HumanTrace

Inspiration

We came upon a news of building collapse in mumbai where inside debris a lot of humnas as well as other livings like piegeons were found this made us think could we create something which can save these lives more rapidly in case of a larger mishappening this led to a marathon of creativity leading to this project

What it does

It takes inputs from a rover which is carrying a thermal sensor and a high resolution camera these inputs will be taken by our machine learning model to search for traces of life , the thermal sensor input will provide us with a range of temperature which will be learned by ml module and will be searched database of different temperature ranges of different species that are found in that area as our goal is to save every life now if the ml module thinks its a living species temperature range it activates the camera module thus giving us another range of inputs to determinenthe livings probability there

How we built it

We built it with help of raspberry pi , tensorflow , c++, python , thermal sensor,camera module and ml module

Challenges we ran into

There were a lot of Challenges including integration of all these modules and relay of information from rover and integrating such vast information giving modules on such a small rover

Accomplishments that we're proud of

We were able to achieve a level of success in doing such a complex project and we are able to learn so much in this field which we were unaware of few years ago

What we learned

We learned how to use and integrate such complex things like thermal sensor , high resolution camera module, raspberry pi and ml module with each other by using tensor flow

What's next for HumanTrace

We will try to reduce size of rover and at the same time increase the range of information relay and make the ml module learn more identifying signatures within these two modules which can help us detect livings faster