FLERT (Fast and Light Emergency Response Toolkit) is a helper for the first responders. This basically keeps a running tally for the number of people in a particular building ( offices, convention centers, houses etc. ) .
This is a very simple entry exit, tally, which communicates to a server ( any public services department can have access to this), the current number of occupants of the building through cloud.
My city (Ahmedabad, India) was hit with an earthquake a few years back. Its a fairly densely populated city. There were numerous buildings which collapsed. The emergency responders were kind of overwhelmed getting all the calls which jammed up the network in a few minutes and it lasted that way for a few hours. In this if there is an easy way for them to know the locations in the city which have a high concentration of people inside a building. Then they would have been able to save a lot more lives.
Each household / community can have the exits equipped with sensors which communicate to an Edison, Galileo, preferably with a LE Bluetooth. The Galileo will communicate with the cloud, every time there is an entry or exit in the premises ( there can be other mechanisms also based on the facility requirement). The Emergency Responders can cross verify the data with a census data to figure out the number of people currently trapped in and focus on the densely populated regions first.
There are numerous other scenarios which can benifit from FL"E"R T. To name a few personal favorites..
Automatically capture the occupancy for places which are crowded and usually have a maximum occupancy limit e.g. clubs, restaurants etc. No more power to the Bouncers, who keep us waiting in lines at clubs :)
Another personal frustration for me is finding a conference room in a large meeting, after having procrastinated booking it thorugh the horrible IT department. This can be so useful in that case. !!!!
Step 1: Step1: Things we used
1) Intel Edison Board
2) IoT Analytics toolkit. ( website registration) https://dashboard.us.enableiot.com/v1/ui/auth#/lo...
3) Extension Board to get easy access to the ports
4) LCD for local monitoring of the data
5) 2 light sensors to validate the entry and exit.
6) Intel Arduino environment to write the code and port it to the Edison Board
7) Patience :)
Step 2: Step 2 : Getting the Hardware Ready
The basic concept of the system is pretty simple
There will be two light sensors on either side of the door. Depending on how the sensors are triggered, a person is either entering or exiting a room.
sensor1 ---- Door ---- sensor2 --- room
If sensor1 is triggered first, then it can be inferred that the person is entering the room.
If Sensor2 is triggered first, then it can be inferred that the person is exiting the room.
We have two leds (red and green) to indicate the entry and exit of the room.
Connect the two sensors on port A0 and A1 of the board.
Connect the two leds on D2 and D3 ports.
The lcd should be connected to the port for the lcd shown in the photo.
Thats it the hardware is setup.
Step 3: Step 3: Getting the Software ready.
Once you have got the hardware working and tested, its time to collect the data and store in the cloud.
The Intel Galileo and Edison kit come with pre-installed IoT Toolkit. This does all the heavy lifting of communicating the data from the registered devices to the cloud. I found this guide very useful when trying to figure things out
The main steps in order to prepare your device to send data are:
1) Create an account on the IOT website.
2) Register your device unique id to the account.
3) Register components you want to track along with the app name.
Follow the steps in the following guide. Its pretty well made.
We used the Arduino software to write our code and push it to the device. We found it to be the easiest way to do.
I am attaching a sample code to get you started for configuring your device and communicating with the toolkit.
Step 4: Credit
This project was done as a part of the hackathon, organized in Mountain View, CA by BeMyApp.
I was a part of 3 member team - me (Falgun Shah) , Aarti Maiya and Preetam Modur.
We got a lot of hands on help from the onsite Intel team and great fellow hackers.
Thanks Everyone. I can give more detailed descriptions and debug help to whatever I can if needed. Please let me know.