About This Project
Thousands of houses are burgled every day in this world. A good percentage of the thieves are even caught later it their faces are caught on CCTV camera. Sometimes even though the thief is seen, he still cant be identified because the face is covered and no finger prints etc are left behind. Is there a way to deal with this situation and bring the instances of burglary down by 50%? We think we have a solution.
iSeeU
Stage 1: Think about this situation, a burglar enters your house thinking/knowing that theres no one in the house. What if there are sensors that detect the intrusion and 3 things happen simultaneously;
CCTV/web camera activates to point in the direction of the movement,
the house owner gets an alert on the phone,
some lights come on in of the room and then go off a couple of times.
Stage 2: Thereafter you can watch the burglar scene using the web cam though your phone. But this is the normal part of the idea.
Stage 3: The innovation here is that you can interact with the burglar using pre-recorded sounds/speeches.
If the burglar is still outside then press the 1st key to activate some lights and play a recording with people loudly whispering, running around and then shouting “thief thief”, and maybe a gun cocking sound. This should send anyone scampering away.
If he’s managed to come inside then press the 2nd key that activates another recording to warn him that he has been caught on camera and with remote recording and therefore he cannot even destroy the footage. It further informs him that if he walks away now then no case will be registered against him and he gets a second chance as a free man. This should be enough to convince 50% of the burglars to go away without anything.
But if he still persists, press the 3rd key that activates another recording with loud sirens going off like a burglar alarm and lights start flashing.
This system should be on a separate power backup source so that even if the mains are cut off, this system will run independently.
The same system has also been rigged up with RFID sensors so that the main door lock is triggered using a servo motor. During the day the system operates as a RFID based entry exit system while in the night as a alarm system .
The RFID system.
This system can be used for entry of family member into the house with valid RFID tag.
the system consists of two RFID scanner present, one for entry and other for exit from the house.
this system can also be used to monitor who is present in the house.
when a person swipes his RF tag on the scanner it triggers the door lock to open and plays audio.
P.S. We are considering working on the option of the homeowner also being able to talk live to the burglar and hear what he has to say too. But this might not be advisable because not everyone will be comfortable in negotiating in this kind of situation.
What’s Connected
3 Ultra-Sonic sensors
2 Rfid modules
USB WebCam
2 Servo Motors
Speaker
Smart Phone
Cayanne
1 Arduino mega with ethernet shield
WEMOS D1
Node MCU
Rasberri Pi
DF Player Mini
Relay
Lights
Triggers & Alerts
there are six trigger and 3 alerts used in this projects.
ALERT:
when the ultrasonc sensor HCSR04 sense distance less than 100 it sends a message notification to the user smartphone.
TRIGGER:
when the RFID tag 1 is scanned on outside RFID scanner , it trigger on the digital actuator(shramik) with virtual pin 6 on the arduino mega, similarly when the RFID tag 1 is scanned on inside RFID scanner, it trigger OFF the digital actuator with virual pin 6 on the arduino mega.
similar trigger are used for digital actuator pratik and hemal.
Scheduling
i have not used scheduling feature of cayenne.
Dashboard Screenshots
Photos of the Project
Raspberry pi connected to local neetwork.
Surveillance camera
RFID scanner outside of the door for entry into the house.
RFID scanner inside the house for exit out .
Servo motor for opening the lock of the door.
message notification
Video
CODE:
home _automation_wemos_code.txt (2.3 KB)
home_automation_mega_code.txt (6.2 KB)
home_automation_nodemcu_code .txt (2.3 KB)