The problem Decentralised Indoor Navigation solves

The main problem this solves is the problem of indoor navigation in public places. This provides efficient routes using a combination of KNN and simple graph algorithms. We obtain the correct paths. One very interesting feature this has is the feature of telling live crowd frequency. How this helps is that the user can automatically know where there is more rush and decide to spend his valuable time elsewhere. We also provide parking location saving. And now since this system is decentralized the maps are automatically built and locations and shops are added to it by investing crypto into this and waiting for more people to give it a vote of confidence. Currently, we have an Indoor Navigation System which has features like crowd analytics, Location suggestion, route suggestion, adding map into the system, Saving parking car locations. We are adding and integrating the blockchain contracts in one or two days.

Challenges we ran into

The main problem that we faced is while developing the ml model to finding the position based on the signals from various access points. We tried our best to solve this by studying various ml models that would suit this.
Also getting the initial data from the access points were difficult to test during the initial stage of development.
processing wifi signal data required a bit of understanding and effort but we were able to solve this after reading many resources.
Another problem we faced is building the contract for this system on Ethereum which is getting very complicated since people can also be differentiated based on the floor. Thus floor number comes in as an additional factor. We are yet to integrate the blockchain script with the system.