scholarly journals Solar Powered Infant Incubator for Assessment in Healthcare System

2021 ◽  
Vol 9 (VI) ◽  
pp. 2403-2410
Author(s):  
S. Rambalaji
Keyword(s):  
Continuous Monitoring ◽  
Human Interaction ◽  
Current Status ◽  
Raspberry Pi ◽  
Huge Number ◽  
Accelerometer Sensor ◽  
Whole Process ◽  
Respective Parent ◽  
Infant Incubator ◽  
Solar Powered

Monitoring baby health status in incubator is a necessary task and need more attention. Huge number of issues was happened previously like improper oxygen supply, theft of child and mishandling in continuous monitoring. Hence a proper automatic system should be needed for monitoring a baby in incubator with reduced human interaction. This can be achieved through sensors and projected as proposed system. Here temperature, humidity, heartbeat, pressure and accelerometer sensor are used to check baby body condition and if any drastic change is identified in it will be automatically intimated through buzzer. If any unauthorized person is picking up the child it will be detected by IR sensor and automatically door will be closed. Another major issue is the current status of a child is not transparent to respective parent here all the details gathered from the sensors will be automatically loaded in cloud through IoT which can viewed by their parent as well as doctor to analyze current status of the baby. The whole process is controlled by Raspberry PI and for continuous monitoring solar panel is added that provide power supply for our system sequentially without any interrupt. Hence it clearly shows that our proposed system achieves the objective of our work and protects baby both in physical and health based parameters.

Monitoring Changes in the Soil and Foundation Characteristics of an Offshore Wind Turbine Using Automated Operational Modal Analysis

2013 ◽  
Vol 569-570 ◽  
pp. 652-659 ◽  
Author(s):  
Gert de Sitter ◽  
Wout Weitjens ◽  
Mahmoud El-Kafafy ◽  
Christof Devriendt
Keyword(s):  
Wind Turbine ◽  
Modal Analysis ◽  
Continuous Monitoring ◽  
Low Frequency ◽  
Operational Modal Analysis ◽  
Human Interaction ◽  
Offshore Wind ◽  
Offshore Wind Turbine ◽  
Support Structure ◽  
Lower Natural Frequency

This paper will show the first results of a long term monitoring campaign on an offshore wind turbine in the Belgian North Sea. It will focus on the vibration levels and resonant frequencies of the fundamental modes of the support structure. These parameters will be crucial to minimize O&M costs and to extend the lifetime of offshore wind turbine structures. For monopile foundations for example, scouring and reduction in foundation integrity over time are especially problematic because they reduce the fundamental structural resonance of the support structure, aligning that resonance frequency more closely to the lower frequencies. Since both the broadband wave energy and the rotating frequency of the turbine are contained in this low frequency band, the lower natural frequency can create resonant behavior increasing fatigue damage. Continuous monitoring of the effect of scour on the dynamics of the wind turbine will help to optimize the maintenance activities on the scour protection system. To allow a proper continuous monitoring during operation, reliable state-of-the-art operational modal analysis techniques should be used and these are presented in this paper. The methods are also automated, so that no human-interaction is required and the system can track the natural frequencies and damping ratios in a reliable manner.

scholarly journals Safety Assistance Visual Surveillance Robot

2020 ◽  
Vol 9 (5) ◽  
pp. 752-756
Keyword(s):  
High Risk ◽  
Object Detection ◽  
Radar System ◽  
Visual Surveillance ◽  
Human Interaction ◽  
Raspberry Pi ◽  
Live Streaming ◽  
Human Beings ◽  
Toxic Environment ◽  
Echo Time

There is a need for safety assistance visual surveillance that can be effectively used to navigate hazardous places which cannot be accessed by human beings. Several high-risk conditions like radioactive zone, toxic environment and accident-prone areas are usually approached/tackled by humans with little to no information about their conditions. Hence our aim is to reduce any human interaction with these unsafe circumstances by proposing a visual surveillance robot that is capable of moving in any terrain and can relay live information to the controller situated at a remote location. In this paper we address the implementation of Visual Surveillance bot by using a Camera that rotates at 360 degree with the help of DC motor, which illustrate the surrounding so as to provide the estimation of danger if any. We present the execution by efficiently live streaming information with the help of Raspberry pi and by using the MATLAB software to create a RADAR plot by analyzing the object detected by Ultrasonic sensor. The usage of MATLAB not only simplifies the analysis but also helps in creating an enhanced RADAR system by using an ARDUINO to support the ultrasonic system in recording the echo time and object detection angle.

Feature Learning Approach for Facial Recognition Using Deep Metric Learning

2020 ◽  
Vol 17 (9) ◽  
pp. 4125-4130
Author(s):  
Gaurav Karkal ◽  
K. Dhanush Reddy ◽  
Kaushik Singh ◽  
Nikith Hosangadi ◽  
Annapurna P. Patil
Keyword(s):  
Neural Network ◽  
Facial Recognition ◽  
Metric Learning ◽  
Feature Learning ◽  
Human Interaction ◽  
Single Image ◽  
Whole Process ◽  
Knn Classifier ◽  
Deep Metric Learning ◽  
Trained Neural Network

Standard deep learning in the context of facial recognition involves inputting a single image and outputting a label for that image. Deep metric learning distinguishes itself by outputting a real valued feature vector instead of a single label. The usage of deep metric learning has revolutionised facial recognition, making it very accurate and reliable. This paper exhibits the accuracy and reliability of the facial recognition model using deep metric learning in the application of an automated attendance system. The paper presents a non-intrusive attendance system which uses the described neural network to recognize faces and record attendance. The system uses the pre-trained neural network to generate embeddings for faces, using a method known as the triple training step, which is described in the paper. These embeddings are generated from a collection of photos per person. After the embeddings are generated, the system is ready to perform facial recognition on sample photos. CNN is used for facial detection in the sample group photos. Once the faces are detected, a KNN classifier is used for recognizing faces. Finally after the faces are recognized, the attendance for each recognized student is marked in the database. Thus, the whole process of attendance was automated without the requirement of human interaction.

scholarly journals Face Recognition Door Lock System using Raspberry Pi

2021 ◽  
Vol 9 (VI) ◽  
pp. 138-145
Author(s):  
K. V. Usha Ramani
Keyword(s):  
Face Recognition ◽  
Face Detection ◽  
Initial Step ◽  
Power Input ◽  
Human Interaction ◽  
Raspberry Pi ◽  
Identification System ◽  
Human Beings ◽  
The Face ◽  
Door Lock

One of the crucial difficulties we aim to find in computer vision is to recognize items automatically without human interaction in a picture. Face detection may be seen as an issue when the face of human beings is detected in a picture. The initial step towards many face-related technologies, including face recognition or verification, is generally facial detection. Face detection however may be quite beneficial. A biometric identification system besides fingerprint and iris would likely be the most effective use of face recognition. The door lock system in this project consists of Raspberry Pi, camera module, relay module, power input and output, connected to a solenoid lock. It employs the two different facial recognition algorithms to detect the faces and train the model for recognition purpose

scholarly journals Design of an Intelligent Management System for Agriculture Monitoring Based on the Internet of Things

2019 ◽  
Vol 8 (12) ◽  
pp. 3948-3950
Keyword(s):  
General Framework ◽  
Human Life ◽  
Water System ◽  
System Innovation ◽  
Current Status ◽  
Raspberry Pi ◽  
Water Utilization ◽  
Intelligent Management ◽  
And Control ◽  
The Internet Of Things

Water is the significant resource in human life. Around 80 % to 90 % water utilized in agriculture field. As because of step by step development in maturation and populace water utilization is additionally increments. There is a challenge before each nation to lessen the ranch water utilization and give new and sound nourishment. Today robotization is one of the significant jobs in human life. The framework isn't just gives comfort yet in addition diminish vitality, proficiency and efficient. At whatever point there is change in warmth, moistness and current status of downpour of the environment these sensors identifies the modification in temperature and stickiness and gives a punctuate sign to the raspberrypi. Presently a day the enterprises are utilizing a computerization and control machines which are high in expense and not appropriate for utilizing in a ranch and nursery turf. So in this work we structure a savvy water system innovation dependent on IOT utilizing Raspberry pi. The framework can be utilized to organize the water engine consequently and can likewise screen the development of plant by utilizing webcam. We can observe live spouting of ranch on mobile phone using machine application by using WirelessFidelity sort out. Raspberrypi is the essential heart of the general framework.

scholarly journals Does exposed JSON data make paid e-songs vulnerable?

2019 ◽  
Author(s):  
Jimut Bahan Pal
Keyword(s):  
Continuous Monitoring ◽  
Fast Rate ◽  
Human Interaction ◽  
Raw Data ◽  
Page Rank ◽  
The Web

JavaScript Object Notation (JSON) is a popular way of interchanging data between the client and servers. It is easy for computers to scan and create JSON objects; is it a secure way of transferring data? If the JSON is exposed, then the answer is no as JSON makes scraping easier. When raw data is scraped from the web it is useless, unless we get the meaningful items from it. With the help of automated bots some companies regularly scrap their competitors’ website for continuous monitoring opponents’ progress, without any human interaction. Google is a good example of scraper which scraps the entire internet at a very fast rate to store in their database, with an intention to implement page rank algorithm that indexes the pages. This paper investigates a popular website, for exposed JSON, to download paid e-songs free of cost. Results show that sites lack security for which it may result in the loss of their earnings.

Surveillance of the Remote Sensitive Areas Using Mobile PIBOT

2018 ◽  
Vol 6 (7) ◽  
pp. 305
Author(s):  
Adila Baseer ◽  
Anil Kumar
Keyword(s):  
Surveillance System ◽  
Continuous Monitoring ◽  
Local Area Network ◽  
Local Area ◽  
Raspberry Pi ◽  
Live Streaming ◽  
Area Network ◽  
System A ◽  
Joint Photographic Experts Group ◽  
Python Programming

In this current world, everyone is worried about their safety due to increase in crime rate. This has led to an increase in the importance of a surveillance system. A system is designed for continuous monitoring and also the system provides live streaming. The system can be deployed at the anyplace i.e. office, house and some remote place where people cannot monitor the particular place. The system acts like a Robot within a local area network through Wi-Fi technology using Raspberry pi 3 , The live streaming is accomplished by using a webcam interfaced with raspberry Pi, it data provided is processed by MJPEG (Motion Joint Photographic Experts Group) streamer and the robot is controlled through webpage’s created. The system is programmed using python programming language.

scholarly journals Using Long-Range Wireless Sensor Network to Track the Illegal Cutting Log

2020 ◽  
Vol 10 (19) ◽  
pp. 6992
Author(s):  
Giva Andriana Mutiara ◽  
Nanna Suryana Herman ◽  
Othman Mohd
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Network Architecture ◽  
Integrated System ◽  
Wireless Sensor ◽  
Raspberry Pi ◽  
Accelerometer Sensor ◽  
Sensing Applications ◽  
Tracking Process ◽  
Hardware Monitoring

Nowadays, the need for wireless sensing applications is increasing. Along with the increased illegal cutting of logs in the forest, however, it requires the integration application to tackle the illegal logging and forest preservation. The wireless sensor network is a suitable network architecture for remotely monitoring or tracking applications in the environment. This paper proposed an integrated system that can identify and track the position of a moving cutting log. An Arduino Uno, Raspberry Pi 3 B+, sound sensor, accelerometer sensor, LoRa GPS HAT Shield, and Outdoor LoRa Gateway OLG01 performed the hardware monitoring and tracking of the proposed system. The network of STAR topology configuration between master and slaves is represented by the LoRa Network embedded with the sensors, as an architecture of the wireless sensor network. The system was examined the performance of the network and the tracking process. The result determined that the LoRa can detect and identify the occurrence of the illegal cutting of logs in real-time. Meanwhile, in terms of the tracking performance, a duration of 5–46 s was required to track the new position of the moving cutting log.

scholarly journals An Optimization Scheme for M2M-Based Patient Monitoring in Ubiquitous Healthcare Domain

2012 ◽  
Vol 8 (4) ◽  
pp. 708762 ◽  
Author(s):  
Sungmo Jung ◽  
Jae Young Ahn ◽  
Dae-Joon Hwang ◽  
Seoksoo Kim
Keyword(s):  
Sensor Networks ◽  
Continuous Monitoring ◽  
Large Scale ◽  
Patient Monitoring ◽  
Human Interaction ◽  
Sensor Data ◽  
Wireless Multimedia ◽  
Optimization Scheme ◽  
Ubiquitous Healthcare ◽  
Multimedia Sensor Networks

In ubiquitous healthcare systems, machine-to-machine (M2M) communication promises large opportunities as it utilizes rapidly developing technologies of large-scale networking of devices for patient monitoring without dependence on human interaction. With the emergence of wireless multimedia sensor networks (WMSNs), M2M communications improve continuous monitoring and transmission and retrieval of multimedia content such as video and audio streams, images, and sensor data from the patient being monitored. This research deploys WMSN for continuous monitoring of target patients and reports tracking for preventive ubiquitous healthcare. This study performs optimization scheme movement coordination technique and data routing within the monitored area. A movement tracking algorithm is proposed for better patient tracking techniques and aids in optimal deployment of wireless sensor networks. Results show that our optimization scheme is capable of providing scalable and reliable patient monitoring results.

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