arduino project

Radar using arduino

DIY Radar using Arduino

arduino project

Components required

Arduino Uno R3 compatible(Buy Now)

Arduino uno R3 is an atemga328p based development board which consist of 13 digital pins and 6 analog pins, This board is one of the most popular development board among the Hobby circuit designers

HC-SR04 Ultrasonic sensor(Buy Now)

HC-SR04 ultrasonic module is generally used t calculate the distance.As name implied this module works by creating ultrasonic sound and the time required to reach its echo(operating range 2cm to 400cm)

Servo Motor SG-90(Buy Now)

Here it gives the swing mechanism 

Jumper Cables

diy radar

Here we use a software to display real time Radar screen in our  computer named as processing3 ( click to download


Arduino code(click here)

Process3 code (click here)

Pins and connections

Servo pins: 

data pin — 12th pin of arduino



Ultrasonic Pins:

Trigger Pin to 10th pin of arduino

Echo pin to 11th pin of  arduino





The smart dustbin is an Arduino based project which is an innovative method to keep the city clean, top of the dustbin will open automatically when a person approaches the dustbin and get closed when he returns

smart dust bin

Working principle

Ultrasonic sensor work based on the ultrasonic sound, ultrasonic sensor continuously monitor the echo signal and detect the obstacle in front of the device if the obstacle is within the threshold range by using a mathematical formula (Distance (in cm) = (duration/2) / 29). then microcontroller and make a decision to open the cap of the dustbin by using a servo motor ,



Face recognition based door locking system

The security sector is experiencing diversification. This has brought about
the need to review the reliability of already existing systems and look into the possibility of creating better systems that are smarter and more secure. The old door security systems made use of keys, locks and chains. However, the locks can be easily broken and keys can get stolen or can be duplicated. In order to overcome this drawback, mechanical locking system was
introduced, that is, latches were used. Latches had better security than the
locks. Although, latches cannot be broken as easily as the locks, they make
the use of keys, which are not so reliable and can get stolen. Further, to
avoid these drawbacks, password based system was introduced. This
system used numeric combination to permit entrance to user.


But security is entirely based on confidentiality and the strength of the password.Modification was made in the password from numeric to alpha-numeric.Security describes protection of life and property. moved to biometric security system to ensure better security. Biometric security system includes fingerprint based system was the first biometric locking system. Using the fingerprints of a person for unlocking the door is main parameter for this system. However, like any other systems, they also have drawbacks. Fingerprints of a person can be duplicated. This can lead to opening of the door for unauthorized person. Finally research moved to image processing system. This system provides high security. When a person wants to access his locker, initially at the main door of locker and PIR sensor will be placed. This sensor will sense the body temperature of a person, standing near the door. And then, his/her image will be captured by
the camera installed at the main gate. This image will be given to the PC
where the Python software will compare this image with the authentic
images stored in the PC. If authentic, then only the door will open otherwise
it will remain closed and the alarm will buzz for further action.


Drowsy driver detection

Drowsy driver detection is one of the potential applications of intelligent vehicle systems. Previous approaches to drowsiness detection primarily make pre-assumptions about the relevant behavior, focusing on blink rate, eye closure, and yawning. Here we employ machine learning to datamine actual human behavior during drowsiness episodes.


Automatic classifiers for facial actions from the facial action coding system were developed using machine learning on a separate database of spontaneous expressions. These facial actions include blinking and yawn motions, as well as a number of other facial movements



Soil prediction for modern agriculture


Agriculture is a non technical sector where in technology can be incorporated for the betterment. Agricultural technology needs to be quick inimplementation and easy in adoption. Farmers usually follow a method called crop mutation after every consequent crop yield. The crop mutation allowsthe soil to regain the minerals that were used by the crop previously and use the left over minerals for cultivating the new crop. To know if the soil hasreached the point where it is unfit to yield the particular crop, farmer has to experience a loss in yield. One financial year for a farmer is very crucial toaccept the loss. This paper implements a that would help in maintaining the soil fertility consistently.


This method is traditionally implemented in manycountries where the change in crop is done after a loss in yield for cultivating the same crop continuously. There are soil parameters that come into consideration when we have to predict the soil quality. This method suggests the solution for the above stated problem using Machine Learning Techniques. This paper suggests a software enabled solution considering crucial soil parameters and soil factors to predict the soil quality.



Hacking prevention for IOT using python

IoT (Internet of Things) is a current technology for sending and receiving the sensor data via internet networks so hacking prevention for IOT is most important in these days. It is same like normal data communication except that in IoT, sensors and microcontrollers are usually used. They are expected to explore, and there will be a growing interest in the IoT platform that provides the common functions of IoT devices.It
Links devices to the Internet and exchanges its data also enables us to monitor and control the real world. IoT systems make use of data in the real world and the data collected from devices can also be a target of cyber-attacks. There are many software solutions existing but technology had changed a lot even software solution can also be in threat.


Project explanation

In this project we propose a device which will act like a hack preventing device and gives an alert to the admin when an attempt is made to hack the IoT deviceIn our product we aim at providing a most secured device which will act like a switch between the IoT devices and the cloud. IoT (Internet of Things) is a current technology for sending a received the sensor data via internet networks. It is same like normal data communication except that in IoT, sensors and microcontrollers are usually used. The sending and receiving of data do not rely on the computer but relies on the microcontroller and portable communication devices such as cell phone, communication pad or even the smart watch with IoT, most of the sensors data can
be directly routed into the server.IoT (Internet of Things) is a collaborative environment of connected, intelligent and context-aware devices. It has been successfully realized as a main part of the 4th industrial revolution based on the rapid development of the cloud, communication technologies, sensor, etc. in contrast with the Ubiquitous. The biggest threat
to the future of IoT is data protection. Hardware in the form of Architectural techniques only. They only detect the attack and there is no preventive measures. It will break the IoT function while a large data flow occur. It is not that much safe to install. In this project we propose a device which will act like a hack preventing device and gives an alert to the
admin when an attempt is made to hack the IoT device it will act like a fuse or a switch that will turn off the connection when there is an excess flow of data through the IOT device and will never crash the IoT device or its data but will disconnect any other hacking sources and makes the system secure.