scholarly journals Design and deployment of relational geodatabase on mobile GIS platform for real-time COVID-19 contact tracing in Ghana

2021 ◽  
Vol 13 (1) ◽  
pp. 126-146
Author(s):  
Seth Kwaku Afagbedzi ◽  
Alex Barimah Owusu ◽  
Isaac Newton Kissiedu ◽  
Mary Amoako-Coleman ◽  
Delia Akosua Bandoh ◽  
...  
Keyword(s):  
Real Time ◽  
Contact Tracing ◽  
Gis Application ◽  
Mobile Gis ◽  
Geographic Coverage ◽  
Field Workers ◽  
Gis Platform

This study reviewed the design and deployment of relational geodatabase on mobile GIS application, using collector for ArcGIS and survey 123 for ArcGIS platforms for COVID-19 contact tracing in Ghana during the lockdown. The study assessed whether cases spread by physical neighborhood contacts, defined by a 2km buffer of initial known 60 cases location. The application was deployed on the android tablet, which was used by field workers. Application Post-deployment review shows that from 30th March to 4th April 2020, 828 samples were collected with 34 confirmed cases, of which 61% occurred outside the 2km buffer. From 1-30 April 2020, 8,748 individuals with 16,087 contacts were tested within the physical neighbourhoods, 2.4% turned positive. Similarly, 7,501 individuals with 17,071 contacts were tested outside the physical neighbourhoods with 4.3% positives.  Results suggest that more infections occurred outside the case’s physical neighbourhoods possibly due to; (1) existence of unknown cases prior to lockdown; (2) cases were moving outside their physical neighborhood and infecting others; (3) panic movements of cases within the 3 days window between announcement and enforcement of lockdown; (4) movement of cases into the country through unapproved routes.  New cases were identified outside the lockdown areas, which could not be explained. This study raises questions about (1) the understanding of the mode of spread of the virus (2) the implementation of the lockdown, including the geographic coverage and timing. It is recommended that future decisions on contact tracing and lockdown should be guided by an understanding of the disease geography. 

IIOT and Real Time Data Analytics - Maximizing the Impact on Safety and Productivity

2021 ◽  
Author(s):  
Ryan Daher ◽  
Nesma Aldash
Keyword(s):  
Real Time ◽  
Case Studies ◽  
Data Analytics ◽  
Contact Tracing ◽  
Time Data ◽  
Seamless Integration ◽  
Location Services ◽  
Industrial Internet ◽  
Potential Applications ◽  
The Impact

Abstract With the global push towards Industry 4.0, a number of leading companies and organizations have invested heavily in Industrial Internet of Things (IIOT's) and acquired a massive amount of data. But data without proper analysis that converts it into actionable insights is just more information. With the advancement of Data analytics, machine learning, artificial intelligence, numerous methods can be used to better extract value out of the amassed data from various IIOTs and leverage the analysis to better make decisions impacting efficiency, productivity, optimization and safety. This paper focuses on two case studies- one from upstream and one from downstream using RTLS (Real Time Location Services). Two types of challenges were present: the first one being the identification of the location of all personnel on site in case of emergency and ensuring that all have mustered in a timely fashion hence reducing the time to muster and lessening the risks of Leaving someone behind. The second challenge being the identification of personnel and various contractors, the time they entered in productive or nonproductive areas and time it took to complete various tasks within their crafts while on the job hence accounting for efficiency, productivity and cost reduction. In both case studies, advanced analytics were used, and data collection issues were encountered highlighting the need for further and seamless integration between data, analytics and intelligence is needed. Achievements from both cases were visible increase in productivity and efficiency along with the heightened safety awareness hence lowering the overall risk and liability of the operation. Novel/Additive Information: The results presented from both studies have highlighted other potential applications of the IIOT and its related analytics. Pertinent to COVID-19, new application of such approach was tested in contact tracing identifying workers who could have tested positive and tracing back to personnel that have been in close proximity and contact therefore reducing the spread of COVID. Other application of the IIOT and its related analytics has also been tested in crane, forklift and heavy machinery proximity alert reducing the risk of accidents.

Personnel Real Time Tracking in Hazardous Areas Using Wearable Technologies and Machine Learning

2021 ◽  
Author(s):  
Tareq Aziz AL-Qutami ◽  
Fatin Awina Awis
Keyword(s):  
Machine Learning ◽  
Real Time ◽  
Communication Systems ◽  
Average Distance ◽  
Location Estimation ◽  
Machine Learning Algorithms ◽  
Contact Tracing ◽  
Localization Algorithm ◽  
Positioning Systems ◽  
Wearable Technologies

Abstract Real-time location information is essential in the hazardous process and construction areas for safety and emergency management, security, search and rescue, and even productivity tracking. It's also crucial during pandemics such as the COVID-19 pandemic for contact tracing to isolate those who came to the proximity of infected individuals. While global positioning systems (GPS), can address the demand for location awareness in outdoor environments, another accurate location estimation technology for indoor environments where GPS doesn't perform well is required. This paper presents the development and deployment of an end-to-end cost-effective real-time personnel location system suitable for both indoor and outdoor hazardous and safe areas. It leverages on facility wireless communication systems, wearable technologies such as smart helmets and wearable tags, and machine learning. Personnel carries the client device which collects location-related information and sends it to the localization algorithm in the cloud. When the personnel moves, the tracking dashboard shows client location in real-time. The proposed localization algorithm relies on wireless signal fingerprinting and machine learning algorithms to estimate the location. The machine learning algorithm is a mix of clustering and classification that was designed to scale well with bigger target areas and is suitable for cloud deployment. The system was tested in both office and industrial process environments using consumer-grade handphones and intrinsically safe wearable devices. It achieved an average distance error of less than 2 meters in 3D space.

Real-time social distance alerting and contact tracing using image processing

2021 ◽  
pp. 297-315
Author(s):  
Balaji Muthazhagan ◽  
Aparnasri Panchapakesan ◽  
Suriya Sundaramoorthy
Keyword(s):  
Image Processing ◽  
Real Time ◽  
Social Distance ◽  
Contact Tracing

scholarly journals Research on Intelligent Supervision Method and System Developing of Soil Remediation Project Based on 3D Mobile GIS

2019 ◽  
Vol 131 ◽  
pp. 01085
Author(s):  
Bin Xie ◽  
Xiangwei Zhao ◽  
Jun Yang ◽  
Qingzhong Wang ◽  
Shun Pan
Keyword(s):  
Real Time ◽  
Soil Remediation ◽  
Metal Content ◽  
System Development ◽  
Mobile Sensors ◽  
Online Interaction ◽  
Effect Analysis ◽  
Mobile Gis ◽  
Gis Technologies ◽  
The Status

At present, some problems such as inconvenient manual supervision, lack of real-time online supervision and poor online interaction during the implementation of soil remediation project. In order to solve the problems, the supervision method and system development of soil remediation project are studied based on sensing online and 3D mobile GIS technologies. The remediation environment are monitored with fixed sensors online and the heavy metal content are sampled with the mobile sensors. The status of soil remediation site is supervised in real time with video online. All the real-time sensing data are integrated and stored in the comprehensive database. The information of soil pollution and remediation environment is visualized with maps and charts in 3D geographic scenes in the system. In addition, the pollution degree evaluation and remediation effect analysis functions are implemented in system. It is proved with the project practice that the method and system are convenient for managers to monitor the environment on-site and supervise the status of soil remediation site in real time. The informationization and intelligence level of soil remediation project can be effectively improved.

scholarly journals Contact tracing with a real-time location system: A case study of increasing relative effectiveness in an emergency department

2017 ◽  
Vol 45 (12) ◽  
pp. 1308-1311 ◽  
Author(s):  
Thomas R. Hellmich ◽  
Casey M. Clements ◽  
Nibras El-Sherif ◽  
Kalyan S. Pasupathy ◽  
David M. Nestler ◽  
...  
Keyword(s):  
Emergency Department ◽  
Real Time ◽  
Relative Effectiveness ◽  
Contact Tracing ◽  
Location System ◽  
System A ◽  
Real Time Location System

scholarly journals Pemetaan Industri di Kota Batam Menggunakan Mobile GIS Berbasis Android

2017 ◽  
Vol 1 (1) ◽  
pp. 1-4
Author(s):  
Zaki A Agha ◽  
Andy Triwinarko ◽  
Baigo Hamuna
Keyword(s):  
Research And Development ◽  
Search Process ◽  
Gis Application ◽  
Mobile Gis ◽  
Digital Maps ◽  
Gis Applications ◽  
Long Time

Android-based mobile GIS application is a service that combines digital maps in vector and smartphone media to search industry in Batam. This application is online. Currently, the information presented only provide location of region, users who are not familiar with the location will be difficult or take a long time to find the location of industry. Therefore it is necessary to design an application that is able to provide information on the location of industries in Batam. This thesis did research and development of Android-based mobile GIS applications to provide information on the location of industry in Batam. These applications have been built with the ability to show a map of Batam are taken from GeoServer, handle the search process, displays information and maps location of industry as desired user.

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