Online ISSN: 2515-8260

Keywords : Raspberry Pi


AN ARTIFICIAL INTELLIGENCE BASED ADVANCED SHRIMP FARMING

S.Jagadeesh Babu; M. Shyam; A. Sivakumar; R. SathyaVignesh; J. Yogapriya

European Journal of Molecular & Clinical Medicine, 2020, Volume 7, Issue 4, Pages 2383-2390

In modern years, the development of technology has been rapidly improving and applying in aquaculture, also known as aqua-farming. A versatile, advanced shrimp farming based on Raspberry pi. A pH sensor, temperature sensor, water level sensor, turbidity sensor are used here to monitor the sudden abnormal change in the condition of the shrimp pond. Besides that, Raspberry pi is used as a server to control all the sensor nodes in this system. The system also sends an alert message through SMS service to prompt the user when needed or to monitor the system on the mobile phone. Thus, time consumption, man power, efforts of the farmer can be reduced. The proposed design has been successfully planned with a dependable, fast response and easy to use with a friendly environment. It is appropriate for small to mid-sized farming operations as it does not require any remodeling of the water front. In this work, a wireless sensor platform is developed, applied to the measurement of temperature, pH and water level in the environment shrimp ponds. The control platform consists of Raspberry pi to control all the system. Then the artificial intelligence system is developed to achieve data from sensor network anywhere via web application as well as Android application. The system is monitored in real-time and can be controlled manually or automatically.

LETHARGY DETECTOR

Subapriya V; Jaichandran R; Usha Kiruthika; Nooka Pujith Sai Kumar Reddy; Chinthkani Saikrishna; Prasingu Bhargav

European Journal of Molecular & Clinical Medicine, 2020, Volume 7, Issue 4, Pages 2808-2814

Lethargy driving is among the primary reason for street mishaps and passing always. along these lines, driver's sleepiness discovery and its sign is a functioning examination zone.

FACE RECOGNITION BASED NEW GENERATION ATM SYSTEM

Dr S Sasipriya; Dr P. Mayil Vel Kumar; S. Shenbagadevi

European Journal of Molecular & Clinical Medicine, 2020, Volume 7, Issue 4, Pages 2854-2865

In the technological advances in financial infrastructure, most bank customers prefer to use Automatic Teller Machines (ATM) for carrying out their banking transactions. To improve the security of these transactions, a new generation ATM machine which is based on face recognition system which replaces ATM card with RFID tag. In this, high quality image has important role in recognition process. Face image is used for authentication purpose. Firstly, the face image of particular person is compared with the database image. Then the compared output result is sent to the control unit through serial communication. If an unauthorized person is identified, an alert message is sent to the corresponding user. Thus, an ATM model which provides security by using Facial verification software by adding up facial recognition systems can reduce forced transactions to a great extent and provide hard-secure authentication. Here Raspberry Pi microcontroller is used in the controlling part

Real time object detection using Image Processing

Dr .S.Joshua Kumaresan; Shaik Shameem; M. Priyadharshini; Mr. Vinodh James; R.Lakshmi Priya

European Journal of Molecular & Clinical Medicine, 2020, Volume 7, Issue 4, Pages 2403-2411

Object detection plays an important role in real time applications. It is used in many applications such as surveillance monitoring, human machine interaction, army base etc. The main aim of this paper is to detect the object and to detect the colour of the object using Image processing technique. Pi camera. Raspberry pi 11 kit interfaced with pi camera is used for detection of object. Raspbian os with python coding is used for object detection and colour recognition.

Efficient Vehicle parking system using Cloud based IoT

SASI PRIYA S; SUMATHI K; ARUN SEKAR R; STEWART KIRUBAKARAN K

European Journal of Molecular & Clinical Medicine, 2020, Volume 7, Issue 4, Pages 2866-2871

The aim of this paper is to develop an intelligent parking system to reduce hiring people's costs and maximize the use of car park owners ' resources. The popular method of finding a parking space is currently manual where drivers typically find a place through luck and experience in the street. This method takes time and energy, which if the driver drives in a city with traffic density, can lead to the worst case of failure and to any parking space. Therefore, through cloud-based IOT and slot allocation through open source computer vision library based recognition tool, a smart car parking system is implemented with slot booking operation. The user can book any of the available slot in the webpage. This system takes away the unpredictability of finding a parking slot. This paper focuses on reducing time wasted on finding parking space nearby and ongoing through the filled parking slots. The end user is provided with a webpage to check the available parking slots. Inside a smart city a smart car parking system is a much needed to save time, fuel and even the environment from pollution.

Implementation of Brain Controlled Robotic Car to Assist Paralytic and physically Challenged People by Analyzing EEG Signals

S. Mahaboob Basha; Gayathri. R; Anjana. J; Joy Sharon. J; R. Pavaiyarkarasi; J. Navin Sankar

European Journal of Molecular & Clinical Medicine, 2020, Volume 7, Issue 4, Pages 2191-2199

In our society, many people are suffering from paralytic diseases which causes several disabilities like they are unable to talk , move physically and also to express their needs. Still, they mostly move their heads and blink their eyes. Based on their ability to blink, we have designed our project which is working under the principle of Brain-Computer Interface (BCI). BCI is based on the direct communication path between the Brain and digital computer. The BCI system enhances the quality of paralytic patients life. BCI which monitors EEG waves from the Brain. EEG –Electroencephalography which observes an Electrical property of the Brain through the Scalp (Noninvasive). The NeuroskyMindwave mobile measures intentionally directed EMG activity (blink strength).
Our proposed system helps them to control the robotic car to the desired place by their eye blink. So they don’t need any caretaker to drive them, they can drive their robotic vehicle themselves. The robotic car starts moving when we run the program; then the direction is chosen by having eye blinks.

IOT ENABLED HEALTH-CAREFOR SENIOR CITIZENS USING FOG COMPUTING

Dr C.M. Velu; Dr T Rajesh Kumar; Dr S.S. Manivannan; Dr Saravanan. M.S; Dr Nelson Kennedy Babu; Dr Shahul Hameed

European Journal of Molecular & Clinical Medicine, 2020, Volume 7, Issue 4, Pages 1772-1779

The IoThealth-care supporting for disabled peoples is an important milestone in technological advancement. In this paper, it is developed a mobile Health-care app, called M-Health, on the system using iPhone with smart Apple watch to help seniors to manage their health life. The proposed M-Health measures the heart rate and notifies to emergency contacts, when it is abnormal. The notification can be a call, SMS, email, or a combination of them. The M-Health suggests the users to take optimum dosage of medicine. This reminds the users to move out for a walk and suggests to perform optimum exercise.Also, it records, heart rate of a patient and sends to the physician periodically. Simulation results shows that, it is beneficial with better performance in avoiding end-to-end delay, resulting excellent throughput of achieving the goal of serving the health-care to the blind, disabled and elderly peoples in time. The results also shows that it is less prone to failure addressing probability of fog computing in IoTenvironment.

AUTONOMOUS STANDALONE FIRE ENGINE WITH LIDAR-ROS

Sivakumar A; Jagadeesh Babu S; Sathya Vignesh R; Shyam M; Yogapriya J

European Journal of Molecular & Clinical Medicine, 2020, Volume 7, Issue 4, Pages 2494-2498

In recent year fire accidents increased rapidly. Firefighting and rescue, is very dangers for firefighters engaged in the field. So robots intended for firefighting have been introduced. However, Robots mobility is limited so it is difficult for them to directly approach fire sources. Here we proposed a solution by designing an autonomous firefighting robot with help of Lidar technology. Lidar can map surrounding environment and create a map of the locality using this pre-map robot can navigate the area by comparing current input from the Lidar. Here each node can be considered as a location point and every building is embedded with number of sensors for fire detection if fire is detected this information is sent to robot. Robot then activates and finds the location by itself and navigate to this location to extinguish fire. The robot-using camera also does fire detection tracking autonomously and water is sprinkled until fire is extinguished.