Technofist provides latest IEEE final year projects for electronics and communication engineering students in MATLAB, Technofist is one of the best final year project institute for electronics and communication engineering students for implementing MATLAB image processing project.
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TMO01
AN INTERNET OF THINGS BASED SMART WASTE MANAGEMENT SYSTEM USING LORA AND
TENSOR FLOW DEEP LEARNING MODEL
ABSTRACT - Traditional waste management system operates based on daily schedule which is highly
inefficientand costly. The existing recycle bin has also proved its ineffectiveness in the public as people
do not recycle theirwaste properly. With the development of Internet of Things (IoT) and Artificial
Intelligence (AI), the traditional waste management system can be replaced with smart sensors embedded
into the system to perform real time monitoring and allow for better waste management. The aim of this
research is to develop a smart waste management system using LoRa communication protocol and
TensorFlow based deep learning model. LoRa sendsthe sensor data and Tensorflow performs real time
object detection and classification. Contact: +91-9008001602 080-40969981
TMO02
AUTOMATED EVALUATION OF COVID-19 RISK FACTORS COUPLED WITH REAL-TIME, INDOOR, PERSONAL
LOCALIZATION DATA FOR POTENTIAL DISEASE IDENTIFICATION, PREVENTION AND SMART QUARANTINING
ABSTRACT - Since the beginning of the current COVID-19 pandemic, more than five million people
have been infected and the numbers are still on the rise. Early symptom detection and proper hygienic
standards are thus of utmost importance, especially in venues where people are in random or opportunistic
contact with each other. To this end, automated systems with medical-grade body temperature
measurement, hygienic compliance evaluation and individualized, person-to-person tracking, are
essential, not only for disease spread intervention and prevention, but also to assure economic stability. Contact: +91-9008001602 080-40969981
TMO03
AUTOMATIC TRAFFIC VIOLATION RECORDING AND REPORTING SYSTEM
ABSTRACT - The quantity of street mishaps increments and causes numerous issues. Numerous
individuals bite the dust and harmed. Likewise, that causes numerous financial, social and mental issues
that have negative effect on the improvement of the world. The primary reason for most of these mishaps
is because of the infringement of the traffic rules: driving with high speeds, crossing a red-light signal, not
keeping adequate separation with the front vehicle in the roadways, driving an inappropriate opposite
way, and so forth. As the number of streets and avenues are huge and the all-out length of these streets is
long, it is extremely unlikely to completely screen every one of them all the time by Traffic Patrol or
camera frameworks. This paper proposes a framework to consequently and self-sufficiently identify and
record the criminal traffic offenses without the help of the individual. Contact: +91-9008001602 080-40969981
TMO04
CONVOLUTION NEURAL NETWORK BASED WORKING MODEL OF SELF DRIVING CAR
ABSTRACT - : A self-driving car is a vehicle that senses its environment and navigates without human
intervention and is a high research topic in computer vision that involves various sub- topics and need to
be deeply reviewed. To accomplish this, our paper discusses hardware and software components of a self
driving car that includes usage of technologies such as Deep learning techniques namely Convolution
Neural Networks, YOLO algorithm, Hough Transform Algorithms, Transfer Learning, Canny Edge
Detection algorithm. Software components such as Arduino IDE, Raspberry Pi Cam Interface, Open CV,
Tensor Flow, Carla simulators and hardware components such as Raspberry Pi 3, Arduino UNO, Pi
Camera, sensors like radar, lidar are used to build a prototype of a self- driving car. Contact: +91-9008001602 080-40969981
TMO05
CROP YIELD PREDICTION USING MACHINE LEARNING ALGORITHM
ABSTRACT - Agriculture is the pillar of the Indian economy and more than 50% of India’s population
are dependent on agriculture for their survival. Variations in weather, climate, and other such
environmental conditions have become a major risk for the healthy existence of agriculture. Machine
learning (ML) plays a significant role as it has decision support tool for Crop Yield Prediction (CYP)
including supporting decisions on what crops to grow and what to do during the growing season of the
crops. The present research deals with a systematic review that extracts and synthesize the features used
for CYP and furthermore, there are a variety of methods that were developed to analyze crop yield
prediction using artificial intelligence techniques. The major limitations of the Neural Network are
reduction in the relative error and decreased prediction efficiency of Crop Yield. Contact: +91-9008001602 080-40969981
TMO06
DESIGN AND IMPLEMENTATION OF AUTOMATIC MEDICINE DISPENSING MACHINE
ABSTRACT - Medicine distribution for the people in the remote tribal areas is finding tedious task for
the Government’s, the Automatic medicine dispensing machine can aid to resolve the above mentioned
requirement. This machine is equipped with some basic and emergency medication and can be refilled. It
is a kind of computerized medicine storage system which can be easily accessed by the people in
emergency without approaching any pharmacy this machine can be easy installed in the remote areas like
long highways, desert areas, remote tribal areas and rural areas. Contact: +91-9008001602 080-40969981
TMO08
DESIGN AND IMPLEMENTATION OF REAL TIME MONITORING OF BRIDGE USING WIRELESS TECHNOLOGY
ABSTRACT - The bridges get damaged due to aging or damage due to natural calamities, the people will
remain unnoticed of it. Then the bridges will be a danger to travel as it can collapse anytime and leads to
disaster. So, continuous bridge checking must be done for better bridge health. For solving this problem, a
design for continuous bridge monitoring has been proposed using wireless IoT technology. This proposed
design helps in monitoring bridges and can also be applied for flyovers. The design consists of monitoring
devices as sensors like load sensor, water level sensor, vibration sensor and tilt sensor which are
interfaced with communication devices. Contact: +91-9008001602 080-40969981
TMO09
DEVELOPMENT OF NONCONTACT BODY TEMPERATURE MONITORING AND PREDICTION SYSTEM FOR
LIVESTOCK CATTLE
ABSTRACT - Annually, numerous cattle die of various diseases, necessitating the need for effective
cattle health management. To ensure cattle disease detection at an early stage and identify the health status
of cattle, we collected the environment temperature, humidity, illuminance, and infrared images of cattle
in an actual-life environment as input parameters to develop an artificial intelligence characterization
module for measuring deep body temperature in a contactless manner. By analyzing the correlation of
estimating deep body temperature at the horn, eyeball, and nose of cattle, the most effective way of
estimating this temperature was found to be at the horn. The estimation accuracy was particularly high in
the sitting state. Contact: +91-9008001602 080-40969981
TMO10
DRIVER ASSISTANCE SYSTEM USING RASPBERRY PI AND
HAAR CASCADE CLASSIFIERS
ABSTRACT - Around 43% of road accidents are due to drowsiness of a driver, says a study by the
Central Road Research Institute (CRRI). Another leading cause for road accidents is drunken driving.
Any amount of alcohol can impact a person’s driving ability and slows their response time. On an average
8 people die every day because of driving under the influence of alcohol. In case of an accident to reduce
the fatalities and get quick emergency response a vehicle crash detection mechanism is necessary. Road
accidents claim nearly three lives every minute, so it is of utmost importance to develop a cost efficient
driver assistance system for automobiles. This will help us to monitor the driver’s physiological
behaviours which will affect the stability of the vehicle and avoid accidents. To implement this, a variety
of software algorithms, input and output extraction hardware tools have been employed in a collaborative
way.
Contact: +91-9008001602 080-40969981
TMO11
DRIVER DROWSINESS MONITORING USING CONVOLUTION NEURAL NETWORKS
ABSTRACT - The advancement in computer vision has assisted drivers in the form of automatic selfdriving cars etc. The misadventure is caused by driver's fatigue and drowsiness about 20%. It poses a
serious problem for which several approaches were proposed. However, they are not suitable for real-time
processing. The major challenges faced by these methods are robustness to handle variation in human face
and lightning conditions. We aim to implement an intelligent processing system that can reduce road
accidents drastically. This approach enables us to identify driver's face characteristics like eye closure
percentage, eye-mouth aspect ratios, blink rate, yawning, head movement, etc. In this system, the driver is
continuously monitored by using a webcam. Contact: +91-9008001602 080-40969981
TMO12
ENHANCED SECURITY MECHANISM FOR ATM MACHINES
ABSTRACT - The project proposes the idea of an image base added security for ATM machines using
Raspberry pi that will eliminate the unauthorized usage of ATM cards by person other than the owner.
The basic idea of the system is that after insertion of the ATM card into the machine and after the card
verification, his image is captured using the webcam in the ATM and then it is matched with the card
owner’s actual images already stored in the database. If the captured image matches with the stored
images, it means he is the authorized user and moves to the next stage where he can enter the password to
continue the transaction. When the stored image and the captured image don’t match, it means that he is
an unauthorized user and thus blocking his access. The system may also inform the actual owner of the
card regarding the card misuse. Contact: +91-9008001602 080-40969981
TMO13
LOW-COST, OPEN-SOURCE MECHANICAL VENTILATOR WITH
PULMONARY MONITORING FOR COVID-19 PATIENTS
ABSTRACT - This paper shows the construction of a low-cost, open-source mechanical ventilator.
The motivation for constructing this kind of ventilator comes from the worldwide shortage of
mechanical ventilators for treating COVID-19 patients—the COVID-19 pandemic has been striking
hard in some regions, especially the deprived ones. Constructing a low-cost, open-source mechanical
ventilator aims to mitigate the effects of this shortage on those regions. The equipment documented
here employs commercial spare parts only. This paper also shows a numerical method for monitoring
the patients’ pulmonary condition. The method considers pressure measurements from the inspiratory
limb and alerts clinicians in real-time whether the patient is under a healthy or unhealthy situation.
Experiments carried out in the laboratory that had emulated healthy and unhealthy patients illustrate
the potential benefits of the derived mechanical ventilator. Contact: +91-9008001602 080-40969981
TMO14
MACHINE LEARNING−BASED ACOUSTIC REPELLENT SYSTEM FOR PROTECTING CROPS AGAINST WILD ANIMAL ATTACKS
ABSTRACT - We present some insights on the issue of crop destruction by wild animals. This is a
serious concern for the affected farmers throughout the world and leads to significant social and financial
distress among them. In order to understand the background of this problem, a survey of Katli village,
Rupnagar, (India) was conducted. The main aim of the current work is to develop a device to protect
crops from damage by wild animals by diverting them from the farms, without harming them physically.
In this context, an Acoustic Repellent System has been designed which uses a convolutional neural
network (CNN) based machine learning model and an IR camera to identify target animals, such as wild
boar, nilgai, and deer. A Raspberry Pi (Rpi) module has been integrated with a camera and a frequency
generator to recognise different animals and produce corresponding frequencies that keep them away from
the farms of interest. Contact: +91-9008001602 080-40969981
TMO15
MECHATRONICS DEVELOPMENT OF TERRESTRIAL MOBILE ROBOT FOR EXPLORING AND MONITORING
ENVIRONMENTAL PARAMETERS AT MINE ANALOGUE SITES USING IOT PLATFORM
ABSTRACT - Mining is one of the main activities in Andean Countries and occupational safety is one of
the most important duties. Despite this, there has been an increase in the number of accidents, even the
mortality rate is still high. Therefore, a Terrestrial Mobile Robot called “MineBot”, integrated with Tele
operation Open-Source technologies, has been proposed for exploring and detecting chemical and
physical as well as biological agents within the underground mines for the purpose of keeping safe the
place for workers. Endowed with both a strong Mechanical design and an intuitive Telerobotic system
applying User Experience design principles as well as Navigation Control, and Environmental Monitoring
systems along with an Internet of Things (IoT) Platform storage. Contact: +91-9008001602 080-40969981
TMO16
A SURVEY ON REDUCING TRAFFIC CONGESTION BY DISSEMINATING MESSAGES IN VEHICULAR AD HOC
NETWORKS
ABSTRACT - Reducing the number of road accidents in the current scenario is a very challenging
societal problem. If the information regarding the accidents is given to the vehicles approaching the area,
the secondary accidents can be considerably reduced. Vehicular Ad Hoc Networks (VANETs), the
network of vehicles that can communicate with each other play a vital role in the reduction of such
accidents. Many survey and research papers published on this topic majorly emphasize on implementation
of VANETs using simulators but this research work is focused on implementation using hardware
components.. Contact: +91-9008001602 080-40969981
TMO17
DESIGN AND IMPLEMENTATION OF THE SMART GLOVE TO AID THE VISUALLY IMPAIRED
ABSTRACT - Locating objects of daily use is a strenuous task for the visually impaired. The objective of
this paper is to design a smart glove by using Deep Neural Networks (DNN) and object tracking algorithm
which will guide the hand of the visually impaired to the desired object in an indoor environment. The
smart glove has five micro-vibrating motors, each one used to guide the user’s hand in five different
directions namely, forward, upward, downward, rightward and leftward. The palm of the glove has a
Universal Serial Bus (USB) camera which feeds the real-time video to the Raspberry Pi for processing.
The camera also has an inbuilt microphone. The user vocally commands the system to identify the desired
object. The camera then detects the object using DNN. Contact: +91-9008001602 080-40969981
TMO18
SMART WIRELESS POWER TRANSMISSION SYSTEM FOR AUTONOMOUS EV CHARGING
ABSTRACT - This paper presents a novel localisation method for electric vehicles (EVs) charging
through wireless power transmission (WPT). With the proposed technique, the wireless charging system
can self-determine the most efficient coil to transmit power at the EV’s position based on the sensors
activated by its wheels. To ensure optimal charging, our approach involves measurement of the transfer
efficiency of individual transmission coil to determine the most efficient one to be used. This not only
improves the charging performance, but also minimises energy losses by autonomously activating only
the coils with the highest transfer efficiencies. The results show that with the proposed system it is
possible to detect the coil with maximum transmitting efficiency without the use of actual power
transmission and comparison of the measured efficiency. Contact: +91-9008001602 080-40969981
TMO19
RASPBERRY PI BASED INTELLIGENT READER FOR VISUALLY IMPAIRED PERSONS
ABSTRACT - The human communication is totally based on speech and text. So visually impaired people
can gather information from voice. With the help of this project visually impaired people can read the text
present in the captured image. In this Project we use Raspberry Pi Camera and this help to take pictures
and that picture is converted into scan image for further process by using Image magick software. The
output of Image magick software is in the form of scanned image this scan image is giving as an input to
the Tesseract OCR (Optical Character Recognition) software to convert image into the text.
For transformation of text into speech we use TTS (Text to Speech) engine. Experimental results shows
that the analysis of different captured images and it will be more helpful to blind people. Contact: +91-9008001602 080-40969981
TMO20
DEEP LEARNING-BASED SIGN LANGUAGE DIGITS RECOGNITION FROM THERMAL IMAGES WITH EDGE
COMPUTING SYSTEM
ABSTRACT - The sign language digits based on hand gestures have been utilized in various applications
such as human-computer interaction, robotics, health and medical systems, health assistive technologies,
automotive user interfaces, crisis management and disaster relief, entertainment, and contactless
communication in smart devices. The color and depth cameras are commonly deployed for hand gesture
recognition, but the robust classification of hand gestures under varying illumination is still a challenging
task. This work presents the design and deployment of a complete end-toend edge computing system that
can accurately provide the classification of hand gestures captured from thermal images. Contact: +91-9008001602 080-40969981
TMO21
REALTIME WIRELESS EMBEDDED ELECTRONICS FOR SOLDIER SECURITY
ABSTRACT - One of the important and vital roles in a country’s defense is played by the army soldiers.
Every year Soldiers get strayed or injured and it is time consuming to do search and rescue operations. In
this paper, we present a WSN-based environmental and health monitoring approach in which sensor data
is processed using robust and stable algorithm implemented in controller. These processed data are then
sent to the base station via low-cost, low- power and secure communication links provided by a LoRa
network infrastructure instead of cellular networks, since, they are either absent or doesn’t allow data
transmission in warzone or remote areas. We focus on monitoring environmental factors such as
temperature, humidity, air pressure, air quality; physical factors such as motion, position, geographic
location and health parameters like ECG (electro cardiograph), blood oxygen level, body temperature.
Moreover, camera and microphone are used to monitor any undesirable situation of soldier. Contact: +91-9008001602 080-40969981
TMO22
DESIGN & IMPLEMENTATION OF REAL TIME AUTONOMOUS CAR BY USING IMAGE PROCESSING & IOT
ABSTRACT - Because of the inaccessibility of Vehicle-to- Infrastructure correspondence in the present
delivering frameworks, (TLD), Traffic Sign Detection and path identification are as yet thought to be a
significant task in self- governing vehicles and Driver Assistance S ystems (DAS ) or Self Driving Car.
For progressively exact outcome , businesses are moving to profound Neural Network Models Like
Convolutional Neural Network (CNN) as opposed to Traditional models like HOG and so forth. Profound
neural Network can remove and take in increasingly unadulterated highlights from the Raw RGB picture
got from nature. In any case, profound neural systems like CNN have a highly complex calculation. Contact: +91-9008001602 080-40969981
TMO23
DEEP LEARNING-BASED SPEED BUMP DETECTION MODEL FOR INTELLIGENT VEHICLE SYSTEM USING
RASPBERRY PI
ABSTRACT - Artificial intelligence in vision based approaches have proven to be effective in various
phases of intelligent vehicle system (IVS). An IVS has to intelligently take many critical decisions in
heterogeneous environment. Speed bump detection is one such issue in real world due to its varying
appearance in dynamic scene. The major issue is the scaling appearance of such objects from far distance
and often viewed as small entity. In the proposed article, deep learning and computer vision based speed
bump detection model is proposed, which assist and control the driving behavior of an IVS before it
reaches to speed bump. Contact: +91-9008001602 080-40969981
TMO24
SMART ROBOTIC PERSONAL ASSISTANT VEHICLE USING RASPBERRY PI AND ZERO UI TECHNOLOGY
ABSTRACT - This paper presents a prototype of a smart robotic personal assistant vehicle based on
Raspberry Pi and Zero-UI technology. Zero UI uses sensory experiences such as gestures, voice and
movement to control the devices. A voice controlled robot vehicle implemented in this paper performs
three functions, viz. movement of the robot is controlled using voice commands; it has the ability to
articulate the text from a captured image using optical character recognition and present the equivalent
audio to the user by using a built-in speaker or headset; it accepts voice commands from the user and uses
Google Assistant API for any query processing and presents information searched on the Internet to the
user in audio form using the built-in speaker or headset. Contact: +91-9008001602 080-40969981
TMO25
SMART CAP FOR VISUALLY IMPAIRED PERSON USING RASPBERRY PI
ABSTRACT - In our surrounding the Communication generally takes place through speech and text. The
aim of this project is to provide an assistive technology to help the visually impaired person usage in
disaster situations. The aim purpose of our paper is to develop a cap for blind which will guide them from
their source to destination. The solution for smart Cap is to support visually Impaired person and it is cost
effective wearable 'smart cap’. The Proposed system consists of web camera which is fitted into a cap,
audio microphone, ultrasonic sensor, Raspberry pi, speaker for voice. The software’s use in this project is
Image processing. open cv, numpy, python. Contact: +91-9008001602 080-40969981
TMO26
SMART OBSTACLE RECOGNITION SYSTEM USING RASPBERRY
ABSTRACT - Blindness is a major problem in the society which made difficult for the person to lead
his/her day-to-day life. The proposed system will detect, track and analyze the approaching objects and
alert them to avoid collision. The PI camera and the Ultrasonic sensor sense the type and distance between
the person and the object. The contactless temperature sensor senses the temperature of the object
contactless manner using infrared rays. The GPS sensor tracks the route and location of the blind and the
ESP8266 connects with the cloud for Realtime monitoring of the blind.
Contact: +91-9008001602 080-40969981
TMO27
A SURVEY ON REDUCING TRAFFIC CONGESTION BY DISSEMINATING MESSAGES IN VEHICULAR AD HOC
NETWORKS
ABSTRACT - Reducing the number of road accidents in the current scenario is a very challenging
societal problem. If the information regarding the accidents is given to the vehicles
approaching the area, the secondary accidents can be considerably reduced. Vehicular Ad Hoc Networks
(VANETs), the network of vehicles that can communicate with each other play a vital role in the
reduction of such accidents. Many survey and research papers published on this topic majorly emphasize
on implementation of VANETs using simulators but this research work is focused on implementation
using hardware components. Henceforth, this research work proposes a real-time system with vehicular
nodes that detects an accident and disseminates the message. Contact: +91-9008001602 080-40969981