scholarly journals AUTOMOTIVE HEALTH TRACKING USING IOT AND ARDUINO

2021 ◽  
Vol 6 (5) ◽  
Author(s):  
Prakhar Prakash
Keyword(s):  
Embedded System ◽  
Health Condition ◽  
Android Application ◽  
Vehicle Owner ◽  
Health Report ◽  
Internal Parameters ◽  
Health Tracking ◽  
Equipment Unit ◽  
Unique Parameter ◽  
Parameter Values

This paper is concerned with the development of an embedded system for detecting the vehicle condition by monitoring the internal parameters used in evaluating the vehicle's current health condition. An in-vehicle embedded system is being developed in this project to generate a vehicle health report (VHR) whenever the user requires it. It predicts future errors, allowing the driver to travel without interruption and avoid accidents. As a result, it warns the driver of potential errors and assists him in driving safely. The data needed to generate the health report is made up of parameter values (outputs of in-built sensors) from various systems inside the vehicle. Our framework is based on the Arduino and IoT stages, which are used to separate various parameters, for example, motor warming and fuel pipe blockage, for safe and cautious driving. The data is sent to IoT, where it can be checked by both the vehicle manufacturer via distributed computing and the vehicle owner via the Android application. The equipment unit consists of an Arduino, a WI-FI module, a portable Androidbased device, and a unique parameter checking sensors module. The ESP8266 WiFi Module is a self-contained SOC with integrated TCP/IP protocol stack that can give any microcontroller access to your WiFi network, which is used in current generation automotive.

scholarly journals Bio Parameters Monitoring System for Sea Researchers using LiFi

2021 ◽  
Vol 9 (VI) ◽  
pp. 5416-5422
Author(s):  
Liya George
Keyword(s):  
Monitoring System ◽  
Health Monitoring ◽  
Health Condition ◽  
Maximum Efficiency ◽  
Wireless Health ◽  
Health Monitoring System ◽  
Scuba Divers ◽  
Communication Method ◽  
Health Monitoring Systems ◽  
Parameter Values

Different types of health monitoring systems are now available in the market. We are using them as a part of our day-to-day life to analyze health conditions. In the case of sea researchers and scuba divers, the medium they are working is water. The health difficulties are more inside the water. So there is a need to develop a health monitoring system for sea researcher’s/scuba divers to analyze their health condition frequently to ensure their safety. The proposed work uses LiFi technology as the communication method to transmit and receive corresponding bio parameter values. This work aims to provide a harmless wireless health monitoring system that will provide maximum efficiency inside the water.

scholarly journals Automatic Number Plate Recognition System Using Optical Character Recognition

2019 ◽  
pp. 986-992 ◽  
Author(s):  
Monika Arora ◽  
Anubha Jain ◽  
Shubham Rustagi ◽  
Tushar Yadav
Keyword(s):  
Embedded System ◽  
Character Recognition ◽  
Optical Character Recognition ◽  
Recognition System ◽  
Traffic Monitoring ◽  
Monitoring And Control ◽  
Monitoring And Control System ◽  
Vehicle Owner ◽  
Optical Character ◽  
And Control

In the last few decades, the number of active vehicle population has increased drastically which has made it difficult for the authorities to keep a track of them as well as to identify the vehicle owner in case of any traffic violation. Automatic Number Plate Recognition System (ANPR) is a real-time machine-intelligent and embedded system which identifies the characters directly from the image of the number plate. Due to crucial research and development of technology and the increasing use of vehicles, the need for a machine-oriented recognition and monitoring system is of immense importance. The technology has become a major requirement and is playing a crucial role in a vast sea of applications related to automated transport monitoring and control system such as traffic monitoring, challan management, detection of stolen vehicles, electronic payment of tolls on highways or bridges, parking lots access control, etc. This technology requires extensive mobility and station flexibility which causes it to be installed on such hardware that is very mobile enough so that the operator can use it very efficiently. ANPR System through the use of Optical Character Recognition (OCR) makes the system to be used as an application on smartphones. This provides the operator to use the system and identify number plates by just capturing the image and processing by neural networks working in the background of OCR. The ANPR system as a whole will result in easy and safe monitoring of the traffic and to keep an easy record in case of any violation. Also, it will save individuals to save their time in standing at long queues at toll taxes and paying cash which will be done with the ANPR system and using E-wallet.

scholarly journals A Real Time Implementation of an IOT based Vehicle Health Monitoring System

2021 ◽  
Vol 10 (3) ◽  
pp. 140-143
Author(s):  
Dr. Hirakjyoti Sarma ◽  
◽  
Dimpal Huzuri ◽  
Dr. Manoj Kumar Deka ◽  
◽  
...  
Keyword(s):  
Embedded System ◽  
Real Time ◽  
Monitoring System ◽  
Health Monitoring ◽  
Evaluation System ◽  
Health Condition ◽  
Primary Objective ◽  
Engine Oil ◽  
Sensor Faults ◽  
Health Monitoring System

This paper approaches an IoT based vehicle health monitoring system that is embedded for detecting the condition of a vehicle by monitoring the internal parameters such as heating rate, engine oil level and status of the CO of the vehicle. It is a real time vehicle health monitoring system is designed and developed to detect and identify the actuator and sensor faults created by automatically or manually by the user of the vehicle. Actually, Vehicles need repair after a certain interval of time and if are not repaired at fixed intervals, it can lead to loss of life of the persons travelling on it and there are many key issues which can affect the vehicle. So, the primary objective of this system is developing an IoT based embedded system that can detect the internal condition of a vehicle by evaluating the various parameters that are used to examine in the vehicle’s current health condition. In fact, this is a real time evaluation system that can be used for rapid condition screening. As a result, it provides all reliable information about the vehicle conditions. This IoT based system claims that it can detect and identify actuator and sensor faults with almost minimal detection latency even after lots of disturbances and uncertainties.

scholarly journals A consensus-based elastic matching algorithm for mapping recall fixations onto encoding fixations in the looking-at-nothing paradigm

2021 ◽  
Author(s):  
Xi Wang ◽  
Kenneth Holmqvist ◽  
Marc Alexa
Keyword(s):  
Data Analysis ◽  
Comparison Method ◽  
Visual Features ◽  
Matching Algorithm ◽  
Image Objects ◽  
Recall Data ◽  
Internal Parameters ◽  
Wide Range ◽  
Speed Up ◽  
Parameter Values

AbstractWe present an algorithmic method for aligning recall fixations with encoding fixations, to be used in looking-at-nothing paradigms that either record recall eye movements during silence or want to speed up data analysis with recordings of recall data during speech. The algorithm utilizes a novel consensus-based elastic matching algorithm to estimate which encoding fixations correspond to later recall fixations. This is not a scanpath comparison method, as fixation sequence order is ignored and only position configurations are used. The algorithm has three internal parameters and is reasonable stable over a wide range of parameter values. We then evaluate the performance of our algorithm by investigating whether the recalled objects identified by the algorithm correspond with independent assessments of what objects in the image are marked as subjectively important. Our results show that the mapped recall fixations align well with important regions of the images. This result is exemplified in four groups of use cases: to investigate the roles of low-level visual features, faces, signs and text, and people of different sizes, in recall of encoded scenes. The plots from these examples corroborate the finding that the algorithm aligns recall fixations with the most likely important regions in the images. Examples also illustrate how the algorithm can differentiate between image objects that have been fixated during silent recall vs those objects that have not been visually attended, even though they were fixated during encoding.

scholarly journals Uncertainty-based automatic calibration of HEC-HMS model using sequential uncertainty fitting approach

2011 ◽  
Vol 14 (2) ◽  
pp. 286-309 ◽  
Author(s):  
S. Jamshid Mousavi ◽  
K. C. Abbaspour ◽  
B. Kamali ◽  
M. Amini ◽  
H. Yang
Keyword(s):  
Simulation Optimization ◽  
Model Verification ◽  
Automatic Calibration ◽  
Hydrologic Models ◽  
Hydrologic Modelling ◽  
North Of Iran ◽  
Unique Parameter ◽  
Parameter Ranges ◽  
Event Based ◽  
Parameter Values

This study presents the application of an uncertainty-based technique for automatic calibration of the well-known Hydrologic Engineering Center-Hydrologic Modelling System (HEC-HMS) model. Sequential uncertainty fitting (SUFI2) approach has been used in calibration of the HEC-HMS model built for Tamar basin located in north of Iran. The basin was divided into seven sub-basins and three routing reaches with 24 parameters to be estimated. From the four events, three were used for calibration and one for verification. Each event was initially calibrated separately. As there was no unique parameter set identified, all events were then calibrated jointly. Based on the scenarios of separately and jointly calibrated events, different candidate parameter sets were inputted to the model verification stage where recalibration of initial abstraction parameters commenced. Some of the candidate parameter sets with no physically meaningful parameter values were withdrawn after recalibration. Then new ranges of parameters were identified based on minimum and maximum values of the remaining parameter sets. The new parameter ranges were used in an uncertainty analysis using SUFI2 technique resulting in much narrower parameter intervals that can simulate both verification and calibration events satisfactorily in a probabilistic sense. Results show that the SUFI2 technique linked to HEC-HMS as a simulation–optimization model can provide a basis for performing uncertainty-based automatic calibration of event-based hydrologic models.

scholarly journals Implementation of IoT in Embedded Systems for Real Time Water Quality Monitoring

2020 ◽  
Vol 9 (4S2) ◽  
pp. 1-4
Keyword(s):  
Embedded System ◽  
Water Quality Monitoring ◽  
Total Dissolved Solids ◽  
Quality Parameters ◽  
Raspberry Pi ◽  
Measured Parameter ◽  
Dissolved Solids ◽  
Quality Of Water ◽  
Ph Level ◽  
Parameter Values

Here we describe an embedded system, its development and design with the help of Raspberry Pi 3 controller that monitors the quality parameters of water which are pH level, turbidity, conductivity, total dissolved solids (TDS) and temperature at the same time. Internet of Things (IoT) technique is employed for the development of the system. Using this system, we have collected the data for the quality of water parameters include: pH level, turbidity, electrical conductivity, total dissolved solids (TDS) and temperature. After processing the data, a short message and email is sent using GSM/GPRS module when the parameters exceed the accepted limit. The efficiency of the system has been checked by comparing the parameter values that are collected using this system with manually measured parameter values in a certified laboratory.

Model and Information Theory Based Diagnostics for Machinery and Gears

2008 ◽  
Author(s):  
Michael D. Bryant ◽  
Ji-Hoon Choi
Keyword(s):  
Information Theory ◽  
Information Flow ◽  
Channel Model ◽  
Functional Condition ◽  
Health Condition ◽  
Ideal Model ◽  
Future Health ◽  
The Real ◽  
Implicit Information ◽  
Parameter Values

Machines focus power. We view a machine as a “machine communications channel,” wherein components along the channel organize power and information flow. Errors from broken or degraded components disrupt this organization and the implicit information processing. Our model based diagnostics approach constructs detailed physics models of the machine having direct physical correspondence to components and faults, measures states off the real in-service machine, simulates states and sensor outputs of the machine under same service loads, compares simulated sensor outputs to real sensor outputs, and adjusts (tunes) the model’s parameters until simulated outputs closely mimic real outputs. The tuned model now contains information on the real system’s health condition. By comparing the numerical values of parameters to those of an ideal model—an exemplar of perfect health—faults are detected and located. To assess machine functional condition, Shannon’s theorems of information theory are applied as a health metric to the machine communications channel. For prognosis of future health, plots of the model’s parameter values extrapolated forward in time predicts future parameter values. Simulation of the machine channel model predicts “future” machine behavior, and future machine functional condition, using the aforementioned methods. This article applies these methods to a gearbox with tooth root cracking.

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