We compiled a set of 30 face images of famous people (7 females and 23 males with ages ranging from 30 to 75) from politics, sports, business and entertainment. The used testing procedure is like the one used for diagnosing of the prosopagnosia a neurological disorder characterized by the inability to recognize human faces. Images of de-identified faces of famous persons are presented to the test subjects with a request to try to recognize them. Obtained answers are recorded for later matching with ground truth answers. The main aim of the performed testing is to evaluate the impact of geometrical and texture modifications on human ability to recognize faces. The evaluation is performed by means of crowdsourcing performed by 150 test subjects (20 females and 130 males). The test subjects were informed that faces in the tests are de-identified faces of famous people. The background (ie context) and biometrical ques like hair and ears, that a user can use for face identification are removed in all tests.

Three main approaches in gait classification i.e. back propagation and KNN. After comparing the testing and training results we get better results using back propagation learning technique. The whole work of paper is to describe the classification technique of different type of GAIT into following four categories: Normal, crouch2, crouch3, crouch4 using back propagation and KNN. When the training of data is done then the output of will be either four options i.e. Normal, crouch2, crouch3, crouch4. If the testing data set is tested on the proposed system then the output must be normal GAIT if the classifier classifies it as normal data or the output will be abnormal GAIT data if the classifier classifies it as crouch2, crouch3, crouch4 in any of these three categories. .

The project would be implemented keeping the teaching industry in mind but could also find its applications in areas that require designing. The basic idea of this project is that a robot would be fed a reference drawing, mostly text-based input or a diagram, which it would then replicate on an output area of our choice for example a white board or a notebook. The benefits of such a robot would be that it would save time that would be required to produce a complex and detailed diagram on a white board for teaching purposes and quite obviously be helpful in graphic designing on materials of our choice if implemented and refined further. The system works on a pulley system where an end-effector is manipulated using the pulleys. The application running on the PC is fed with the image which the recognizes the edges of the image and then sends command numbers to the microcontroller. The microcontroller upon receiving the command numbers performs commands associated with the received command numbers. The microcontroller rotates the stepper motor as per the need of the image to be drawn, the servo motor attached at the pen-holder acts as a pen lifting mechanism similar to the action we perform while writing or drawing. The pulley system adds to the maneuverability of the system while cutting down on costs. The system works as per predicted and produces good quality drawings on the drawing pad.

The Field of Artificial Intelligence is very vast but the prime goal of researchers and engineers is to enable the computer to think like a human. And a game of chess require a lot of thinking and logic, for a long time we have been playing the game of chess to exercise our brains and entertain ourselves at the same time. And we all love the feel of an original chess board. It would be really nice to play the game of chess against an Physical Board. Using the core XY motion of two motors we are enabling an electromagnet to span a whole chess board and the electromagnet will be responsible to slide the pieces across the whole board. Using two Nema 17 motors and two lead screw mechanism for our X and Y axises both powered by L2N8 motor drivers and a relay module to control the electromagnet the chess pieces with sufficiently strong magnets attached to the bottom will slide across the board. Using the Min-Max spanning tree providing an initial score to each player the goal of our AI is to minimize the score of the opposing player and trying to maintain its own score. User will make a move and depending on the move made by user our AI will generate a move tree containing possible moves. Every piece of the board has a rank and a score which is equal to the sum of all the ranks of alive pieces of that particular color will be assigned at each step to the color. Each node of the move tree contains the score corresponding to the move, treating scores as weights of the tree we apply Min-Max search to make the best possible move.

Autonomous driving has passed the point of being called the biggest step, as the smart car revolution is already taking shape around the world. Self-driving cars are relevant if not prevalent and the biggest obstacles to reach the mass adoption are customer acceptance, cost, infrastructure and the reliance on several onerous algorithms that include perception, lane marking detection, path planning and variation in pathways. In this research, authors have used most popular method of deep learning i.e. Convolution Neural Network (CNN) to train the collected data on the VGG16 model. Later these have optimized directly by the proposed system with cropping each unnecessary image and mapping pixels from a single front-facing camera to direct steering instructions. It has been observed from the experimental work that proposed model has given better result than the existing work i.e. increase in the accuracy from 88% (Udacity training dataset) to 98% (proposed). This model is suitable for industrial use and robust in real time scenarios therefore can be applied in modern industrialized systems.

The arm control by robotics is very popular in the world of robotics. The essential part of the robotic arm is a programmable micro controller-based brick capable of driving basically four servos to form an anthropomorphic structure. Our primary objective is to make the Robotic arm, having 4 servo motors to interface with the development of a microcontroller based Robotic arm. It provides more interfaces to the outside world and has larger memory to store many programs. The technology for assisting people who are functionally challenged has improved over the recent decades. A group that suffer from this ailment are people with Parkinson’s disease. Parkinson’s disease (PD) is a neurological degenerative disease that causes uncontrollable shaking and makes it difficult for the affected person to eat. There is no cure for PD, but there is technology and potential for new technology that can help people who carry the disease with their daily lives. The machine will be of great use to perform repetitive tasks of picking and placing of small edibles upto 500 grams in one serving. It can be used to do small assembly work effectively due to its great added accuracy for placement purpose, which has further extended scope of our project.

When a medical emergency takes place in natural flood, the response time can make all the difference between a life saved and a life lost. Unfortunately, ambulances can’t reach in the place due to over water flooding, in which time a cardiac arrest victim may have already succumbed to a lack of oxygen to the brain. Drone is an all-purpose medical toolkit that can be automatically flown to any emergency situation and used to guide citizens to make non-technical lifesaving procedures. With our drone we dramatically increase this survival rate. The incorporation of a two-way, video supported, communication channel in the drone between operators and the first responders will improve first care. Successful drone usage by lay-persons is currently at 20%. With personalized instructions and communication on the drone, this can be increased to 90%. In short, the drone helps to save lives by extending existing emergency infrastructure with a network of fast and compressed video broadcasting channel capable of bringing emergency supplies and establishing communication between dedicated source and destination.

Our project is a smartphone-based sleep staging system with two main components: the application and the EEG band. The EEG band can be connected to the smartphone using Bluetooth, which sends the EEG signals to the phone for analysis of the sleeping user. The application then scores the sleep presenting the information to the user to infer their sleeping patterns. It can also be used for development of user interface that triggers stimuli in specific sleep stages based on further improvements. The project employs the use of a Machine Learning model paired with a smartphone to analyse the EEG input, allowing for classification of the sleep stage of a person. We will be using an EEG with wireless functionality. The project has been divided into 4 phases: Research, ML model development, Android app development and Testing/Improvements.

The weather can have great impact on lives. Weather changes can influence wide range of human activities and affect agriculture and transportation. The project’s objective is to monitor and report weather conditions so that one is informed beforehand and necessary actions can be taken to reduce the damage by any calamity by forecasting it. Through weather monitoring system we can collect the information according to current and previous data we can produce the results in graphical manner. In addition to this, there is one research paper that has discussed monitoring these three environmental conditions; however, there has been no mention about having actuators to modify. So, our main idea was to coin a system that can sense the main components that formulates the weather and can be able to forecast the weather without human error. We will be analyzing temperature, pollutants, humidity and pressure and will predict the weather. Existing models are expensive in contrast to ours and hence it will make monitoring local area feasible as it will be cheaper.

In the age of digitalization, Internet-based applications are gaining popularity at an exponential rate. Today, everyone wants to make their lives easier and devices smarter. In the age of automation, most of the devices we interact with on a day-to-day basis, for example, air conditioners, refrigerators, etc. are made increasingly intelligent to simplify our lives and make it comfortable. Using the principles of IoT and AI, we can create home automation devices such as automatic security devices and e-meters that make our homes smarter and more secure. Keeping a track of how much electricity is consumed per household becomes imperative seeing the rate at which global warming is increasing. Gone are the days where users had to go to meter reading room and take down readings. By employing IoT concepts, we can simplify this tedious process and record the reading over cloud for easy accessibility. The major advantage of digitalizing the process is that the user has the facility to view his consumption remotely, i.e., anywhere in the world. This also enables the user to keep a log of how many units of electricity a device is consuming and with how much amount the user is being charged fairly or not. Also, it was observed that the new system was more accurate and faster than the existing systems. By simple application of IoT principles, current sensor, and microcontrollers, we have streamlined the process and moved the process to a cloud-based application. This not only provides remote accessibility but also accountability and reliability.

In the age of digitalization, Internet-based applications are gaining popularity at an exponential rate. Today, everyone wants to make their lives easier and devices smarter. In the age of automation, most of the devices we interact with on a day-to-day basis, for example, air conditioners, refrigerators, etc. are made increasingly intelligent to simplify our lives and make it comfortable. Using the principles of IoT and AI, we can create home automation devices such as automatic security devices and e-meters that make our homes smarter and more secure. Keeping a track of how much electricity is consumed per household becomes imperative seeing the rate at which global warming is increasing. Gone are the days where users had to go to meter reading room and take down readings. By employing IoT concepts, we can simplify this tedious process and record the reading over cloud for easy accessibility.

The inevitability of robots is fundamentally a result of the need to reduce manpower requirements in military organizations, while sustaining the capability needs of the organizations. The need to reduce manpower is driven by the trends of the macro environment for military organizations, which include the aging demographics and reducing public tolerance to human casualties. The evolving operational environment that places increasing demands on soldiers and exposes the limitations of the human body also supports the adoption of robots.