scholarly journals An Intelligent System to Enhance Visually-Impaired Navigation and Disaster Assistance using Geo-Based Positioning and Machine Learning

2021 ◽  
Author(s):  
Wenhua Liang ◽  
Ishmael Rico ◽  
Yu Sun
Keyword(s):  
Machine Learning ◽  
Global Positioning System ◽  
Visually Impaired ◽  
Intelligent System ◽  
Positioning System ◽  
Technological Advancement ◽  
Disaster Assistance ◽  
Global Positioning ◽  
New Phase ◽  
Do So

Technological advancement has brought many the convenience that the society used to lack, but unnoticed by many, a population neglected through the age of technology has been the visually impaired population. The visually impaired population has grown through ages with as much desire as everyone else to adventure but lack the confidence and support to do so. Time has transported society to a new phase condensed in big data, but to the visually impaired population, this quick-pace living lifestyle, along with the unpredictable natural disaster and COVID-19 pandemic, has dropped them deeper into a feeling of disconnection from the society. Our application uses the global positioning system to supportthe visually impaired in independent navigation, alerts them in face of natural disasters, and remindsthem to sanitize their devices during the COVID-19 pandemic.

scholarly journals An Intelligent System for the Enhancement of Visually Impaired Navigation and Disaster Assistance using Geo-Based Positioning and Machine Learning

2021 ◽  
Vol 12 (3) ◽  
pp. 1-15
Author(s):  
Wenhua Liang ◽  
Ishmael Rico ◽  
Yu Sun
Keyword(s):  
Global Positioning System ◽  
Visually Impaired ◽  
Intelligent System ◽  
Positioning System ◽  
Technological Advancement ◽  
Disaster Assistance ◽  
Global Positioning ◽  
The Masses ◽  
New Phase ◽  
Do So

Technological advancement has brought the masses unprecedented convenience, but unnoticed by many, a population neglected through the age of technology has been the visually impaired population. The visually impaired population has grown through ages with as much desire as everyone else to adventure but lack the confidence and support to do so. Time has transported society to a new phase condensed in big data, but to the visually impaired population, this quick-pace living lifestyle, along with the unpredictable nature of natural disaster and COVID-19 pandemic, has dropped them deeper into a feeling of disconnection from the society. Our application uses the global positioning system to support the visually impaired in independent navigation, alerts them in face of natural disasters, and reminds them to sanitize their devices during the COVID-19 pandemic.

Machine learning methodology for TEC prediction using global positioning system signal measurements

2020 ◽  
Author(s):  
S.G. Prasad Mutchakayala ◽  
V.L. Manasa Mandalapu ◽  
J.R.K. Kumar Dabbakuti ◽  
Sai Sruti Vedula
Keyword(s):  
Machine Learning ◽  
Global Positioning System ◽  
Positioning System ◽  
Global Positioning

scholarly journals Wheel Obstraction Detection with Machine Learning

2019 ◽  
Vol 8 (9S4) ◽  
pp. 267-274
Keyword(s):  
Machine Learning ◽  
Global Positioning System ◽  
Positioning System ◽  
Assessment Framework ◽  
Special Cases ◽  
Global Positioning ◽  
Quantitative Examination ◽  
Separation Size ◽  
Special Case

In this paper, to blessing an ongoing programmed innovative and insightful based absolutely rail assessment framework, which plays examinations at sixteen km/h with a casing rate of 20 fps. The framework identifies significant rail segments including ties, tie plates, and grapples, with high exactness and productivity. To accomplish this objective, to initially widen an immovable of picture and video investigation and after that prompt a particular worldwide streamlining structure to join proof from two or three cameras, Global Positioning System, and separation size apparatus to moreover improve the recognition execution. Additionally, as the grapple is a significant kind of rail clasp, to've as needs be propelled the push to hit upon stay special cases, which consolidates evaluating the grapple circumstances on the tie stage and recognizing grapple design exemptions on the consistence level. Quantitative examination performed on a huge video certainties set caught with unmistakable tune and lighting installations conditions, notwithstanding on a continuous order check, has affirmed empotoring execution on each rail perspective recognition and stay special case location. In particular, a middle of 94.67% accuracy and ninety three% remember expense has been finished for recognizing each of the 3 rail segments, and a 100% recognition charge is practiced for consistence level stay special case with three phony positives predictable with hour. To our excellent comprehension, our framework is the essential to address and clear up both perspective and special case location issues in this rail assessment region

A Remote Vision Guidance System for Visually Impaired Pedestrians

2006 ◽  
Vol 59 (3) ◽  
pp. 497-504 ◽  
Author(s):  
Z. Hunaiti ◽  
V. Garaj ◽  
W. Balachandran
Keyword(s):  
Global Positioning System ◽  
Mobile Networks ◽  
Visually Impaired ◽  
Guidance System ◽  
Geographical Information ◽  
Positioning System ◽  
The Third ◽  
Vision Guidance ◽  
Global Positioning ◽  
Technological Platform

This paper presents research and development work on a novel system with a view of developing a navigation system for the guidance of visually impaired pedestrians. The prime aim of the new developed system is to enhance the mobility of visually impaired pedestrians using remote guidance provided by sighted person. However, the system can be used in many other applications. The system implementation is based on the integration of the Global Positioning System (GPS), Geographical Information System (GIS) database and a remote vision facility over the third generation (3G) of mobile networks, providing a technological platform enabling visually impaired pedestrians to be guided remotely by a sighted guide.

scholarly journals A Method to Estimate Horse Speed per Stride from One IMU with a Machine Learning Method

Sensors ◽  
2020 ◽  
Vol 20 (2) ◽  
pp. 518 ◽  
Author(s):  
Amandine Schmutz ◽  
Laurence Chèze ◽  
Julien Jacques ◽  
Pauline Martin
Keyword(s):  
Machine Learning ◽  
Global Positioning System ◽  
Learning Model ◽  
External Input ◽  
Smart Device ◽  
Positioning System ◽  
Machine Learning Method ◽  
Learning Method ◽  
Machine Learning Model ◽  
Global Positioning

With the emergence of numerical sensors in sports, there is an increasing need for tools and methods to compute objective motion parameters with great accuracy. In particular, inertial measurement units are increasingly used in the clinical domain or the sports one to estimate spatiotemporal parameters. The purpose of the present study was to develop a model that can be included in a smart device in order to estimate the horse speed per stride from accelerometric and gyroscopic data without the use of a global positioning system, enabling the use of such a tool in both indoor and outdoor conditions. The accuracy of two speed calculation methods was compared: one signal based and one machine learning model. Those two methods allowed the calculation of speed from accelerometric and gyroscopic data without any other external input. For this purpose, data were collected under various speeds on straight lines and curved paths. Two reference systems were used to measure the speed in order to have a reference speed value to compare each tested model and estimate their accuracy. Those models were compared according to three different criteria: the percentage of error above 0.6 m/s, the RMSE, and the Bland and Altman limit of agreement. The machine learning method outperformed its competitor by giving the lowest value for all three criteria. The main contribution of this work is that it is the first method that gives an accurate speed per stride for horses without being coupled with a global positioning system or a magnetometer. No similar study performed on horses exists to compare our work with, so the presented model is compared to existing models for human walking. Moreover, this tool can be extended to other equestrian sports, as well as bipedal locomotion as long as consistent data are provided to train the machine learning model. The machine learning model’s accurate results can be explained by the large database built to train the model and the innovative way of slicing stride data before using them as an input for the model.

scholarly journals Personal Guidance System for People with Visual Impairment: A Comparison of Spatial Displays for Route Guidance

2005 ◽  
Vol 99 (4) ◽  
pp. 219-232 ◽  
Author(s):  
Jack M. Loomis ◽  
James R. Marston ◽  
Reginald G. Golledge ◽  
Roberta L. Klatzky
Keyword(s):  
Visual Impairment ◽  
Global Positioning System ◽  
Navigation System ◽  
Visually Impaired ◽  
Guidance System ◽  
Location Information ◽  
Positioning System ◽  
Route Guidance ◽  
Subjective Ratings ◽  
Global Positioning

This article reports on a study of route guidance using a navigation system that receives location information from a Global Positioning System receiver. Fifteen visually impaired participants traveled along 50-meter (about 164-foot) paths in each of five conditions that were defined by the type of display interface used. One of the virtual displays—virtual speech—led to the shortest travel times and the highest subjective ratings, despite concerns about the use of headphones.

scholarly journals GPS NAVIGATOR FOR VISUALLY IMPAIRED

2013 ◽  
pp. 250-253
Author(s):  
MANDAR GAUDE ◽  
VIRESH CANDOLKAR
Keyword(s):  
Global Positioning System ◽  
Navigation System ◽  
Visually Impaired ◽  
Positioning System ◽  
Global Positioning ◽  
Impaired User ◽  
Impaired Person

The objective of this study is the development of navigation system which supports activities of the visually impaired without help of others. This system navigates a visually impaired person by using information about GPS (Global Positioning system). In this navigation system, after setting the destination, position of user is obtained by GPS and a visually impaired user is guided along the predefined route.

GPS/INS Integration During GPS Outages Using Machine Learning Augmented with Kalman Filter

2021 ◽  
Vol 16 ◽  
pp. 294-301
Author(s):  
Reshma Verma ◽  
Lakshmi Shrinivasan ◽  
K Shreedarshan
Keyword(s):  
Machine Learning ◽  
Kalman Filter ◽  
Global Positioning System ◽  
Navigation System ◽  
Inertial Navigation System ◽  
Inertial Navigation ◽  
Supervised Machine Learning ◽  
Positioning System ◽  
Position Information ◽  
Global Positioning

Nowadays a tremendous progress has been witnessed in Global Positioning System (GPS) and Inertial Navigation System (INS). The Global Positioning System provides information as long as there is an unobstructed line of sight and it suffers from multipath effect. To enhance the performance of an integrated Global Positioning System and Inertial Navigation System (GPS/INS) during GPS outages, a novel hybrid fusion algorithm is proposed to provide a pseudo position information to assist the integrated navigation system. A new model that directly relates the velocity, angular rate and specific force of INS to the increments of the GPS position is established. Combined with a Kalman filter the hybrid system is able to predict and estimate a pseud GPS position when GPS signal is unavailable. Field test data are collected to experimentally evaluate the proposed model. In this paper, the obtained GPS/INS datasets are pre-processed and semi-supervised machine learning technique has been used. These datasets are then passed into Kalman filtering for the estimation/prediction of GPS positions which were lost due to GPS outages. Hence, to bridge out the gaps of GPS outages Kalman Filter plays a major role in prediction. The comparative results of Kaman filter and extended Kalman filter are computed. The simulation results show that the GPS positions have been predicted taking into account some factors/measurements of a vehicle, the trajectory of the vehicle, the entire simulation was done using Anaconda (Jupyter Notebook).

scholarly journals Design & Implementation of Intelligent System for Identification of Fuel Fraudulents and Near by Fuel Stations

2019 ◽  
Vol 8 (2) ◽  
pp. 1515-1518
Keyword(s):  
Global Positioning System ◽  
Mobile Communication ◽  
Intelligent System ◽  
Threshold Value ◽  
Positioning System ◽  
Filling Process ◽  
Through Flow ◽  
Global Positioning ◽  
Lcd Display ◽  
Rate Sensor

The increasing frauds in fuel filling process have become a big deal to the society. The pumps in petrol bunks are controlled with the end goal that it shows the fuel filled into vehicle as entered, yet the amount of fuel filled is not exactly shown by the display. The petrol bunk proprietors are making enormous benefits by tricking the clients. This is redressed through estimation of approaching fuel through flow rate sensor and showing it on the LCD display and the measured output is sent as a message by means of global system for mobile communication (GSM) technology to the enlisted user for undeniable record can be made. This would help the proprietors of transportation companies to keep up a record of their vehicles that are run by their paid drivers. if the petrol in the tank is less than threshold value then LED glows continuously until the petrol is filled and it display the distance of the nearby petrol bunks by using the global positioning system (GPS) and is displayed on LCD.

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