scholarly journals Design and Deployment of Vehicular Internet of Things for Smart City Applications

2021 ◽  
Vol 14 (1) ◽  
pp. 176
Author(s):  
Evariste Twahirwa ◽  
James Rwigema ◽  
Raja Datta
Keyword(s):  
Internet Of Things ◽  
Real Time ◽  
Vehicular Networks ◽  
Historical Data ◽  
Low Cost ◽  
Urban Transport ◽  
Transport Systems ◽  
Vehicular Communication ◽  
Sensors And Actuators ◽  
Web Based

A novel computing paradigm, called the Internet of things emerged a few years ago. IoT is materialized by connecting both real and digital worlds together. The deployment of IoT in vehicular networks has introduced a new vehicular communication technology-themed vehicular internet of things (V-IoT). With the introduction of miniaturized sensors and actuators, V-IoT has demonstrated the ability to improve the level of urban transport systems through the development and deployment of low-cost but powerful technologies which seamlessly upgrade the level of smart transportation in urban environments. In this research article, we have presented the features of V-IoT that encompass both the benefits and potential challenges of the technology. Low-cost IoT prototypes have been built and tested for numerous functions in vehicular environments. The monitored parameters include air, road conditions such as traffics flow sizes, air quality, weather parameters, and signal status in terms of Received signal strength indicator, and Signal noise ratio for both road and intra-vehicular environments. Devices are implemented at every IoT architectural layer and tested on a web-based IoT front-end application using different protocols like LoRaWAN. Two LoRa sensors have been deployed in the public bus to monitor some of the mentioned parameters on a real-time basis and historical data could be retrieved through the developed web-based dashboard. Simplistic algorithms are implemented for both real-time and historical data demonstration.

An Information and Cooperation Portal for Supporting Public Authorities and Organizations with Safety and Security Responsibilities Before and During Large Public Events

2013 ◽  
pp. 335-344
Author(s):  
Sandra Frings ◽  
David López Remondes ◽  
Wolf Engelbach
Keyword(s):  
Urban Transport ◽  
Transport Systems ◽  
Event Analysis ◽  
Event Management ◽  
Public Authorities ◽  
Web Based ◽  
Security Issues ◽  
Public Events ◽  
Communication Processes ◽  
Technical Issues

Large public events are quite common and lead to peak usage of urban transport systems. Clear planning and communication processes which involve relevant parties for event management, traffic and security issues are needed due to the increasing number and complexity of events. When planning an event, overall organizational and technical issues as well as the preparation for unexpected incidents are asked for to plan for maximum safety and security. Within the research project VeRSiert1, a web-based information and cooperation portal was designed for the region of Cologne and implemented for these purposes. Its intention is to support collaboration of the participating organizations prior to, during execution and post-event analysis of a large public event, while taking into account unplanned risks ranging from storms to acts of terrorism.

scholarly journals Utilization of programmable cameras for web-based sensing and control of daylight in buildings

2021 ◽  
Vol 2042 (1) ◽  
pp. 012114
Author(s):  
Dongjun Mah ◽  
Michael Kim ◽  
Athanasios Tzempelikos
Keyword(s):  
Real Time ◽  
Computational Efficiency ◽  
Low Cost ◽  
Visual Environment ◽  
Rear Side ◽  
Web Based ◽  
Computer Screen ◽  
And Control ◽  
Sky Conditions ◽  
Camera Sensors

Abstract The concept of integrating programmable low-cost cameras into the office infrastructure and BMS for real-time, web-based sensing and control of the luminous environment in buildings is presented in this study. Experiments were conducted to evaluate the potential of predicting the luminance field perceived by an office occupant using a programmable calibrated HDR camera installed at the rear side of a computer monitor or on the wall behind the occupant, for a variety of sky conditions and shading options. The generated luminance maps using Python scripts with OpenCV packages were further processed to extract daylighting and glare metrics using Evalgare. The results showed that: (i) among the different camera resolutions that were compared, the 330x330 resolution was selected as the best option to balance between accurate capturing of visual environment and comfort and computational efficiency; (ii) a camera sensor embedded on the rear side of a computer screen could capture interior visual conditions consistently similarly to those viewed by the occupant, except for sunny conditions without proper shading protection. This prototype study paves the way for luminance monitoring and daylight control using programmable low-cost camera sensors embedded into the office infrastructure.

scholarly journals IOTFlood: hardware and software platform using internet of things to monitor floods in real time

2021 ◽  
Vol 16 (4) ◽  
pp. 1
Author(s):  
Francisco Vital Da Silva Júnior ◽  
Mônica Ximenes Carneiro Da Cunha ◽  
Marcílio Ferreira De Souza Júnior
Keyword(s):  
Internet Of Things ◽  
Real Time ◽  
Monitoring System ◽  
Research Design ◽  
Open Source Software ◽  
Low Cost ◽  
Sensor Data ◽  
Software Platform ◽  
Web Interface ◽  
Iot Platform

Floods are responsible for a high number of human and material losses every year. Monitoring of river levels is usually performed with radar and pre-configured sensors. However, a major flood can occur quickly. This justifies the implementation of a real-time monitoring system. This work presents a hardware and software platform that uses Internet of Things (IoTFlood) to generate flood alerts to agencies responsible for monitoring by sending automatic messages about the situation of rivers. Research design involved laboratory and field scenarios, simulating floods using mockups, and later tested on the Mundaú River, state of Alagoas, Brazil, where flooding episodes have already occurred. As a result, a low-cost, modular and scalable IoT platform was achieved, where sensor data can be accessed through a web interface or smartphone, without the need for existing infrastructure at the site where the IOTFlood solution was installed using affordable hardware, open source software and free online services for the viewing of collected data.

scholarly journals Scalable System for Smart Urban Transport Management

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Nauman Ahmad Khan ◽  
Jean-Christophe Nebel ◽  
Souheil Khaddaj ◽  
Vesna Brujic-Okretic
Keyword(s):  
Real Time ◽  
Large Scale ◽  
High Volume ◽  
Heterogeneous Data ◽  
Urban Transport ◽  
Capital City ◽  
Strategic Decision ◽  
Sensor Data ◽  
Transport Systems ◽  
Transport Management

Efficient management of smart transport systems requires the integration of various sensing technologies, as well as fast processing of a high volume of heterogeneous data, in order to perform smart analytics of urban networks in real time. However, dynamic response that relies on intelligent demand-side transport management is particularly challenging due to the increasing flow of transmitted sensor data. In this work, a novel smart service-driven, adaptable middleware architecture is proposed to acquire, store, manipulate, and integrate information from heterogeneous data sources in order to deliver smart analytics aimed at supporting strategic decision-making. The architecture offers adaptive and scalable data integration services for acquiring and processing dynamic data, delivering fast response time, and offering data mining and machine learning models for real-time prediction, combined with advanced visualisation techniques. The proposed solution has been implemented and validated, demonstrating its ability to provide real-time performance on the existing, operational, and large-scale bus network of a European capital city.

scholarly journals Network Management and Monitoring Solutions for Vehicular Networks: A Survey

Electronics ◽  
2020 ◽  
Vol 9 (5) ◽  
pp. 853 ◽  
Author(s):  
João Dias ◽  
Joel Rodrigues ◽  
Vasco Soares ◽  
João Caldeira ◽  
Valery Korotaev ◽  
...  
Keyword(s):  
Vehicular Networks ◽  
Low Cost ◽  
Efficient Solutions ◽  
Transport Systems ◽  
Intelligent Transport Systems ◽  
Node Density ◽  
Intelligent Transport ◽  
Comprehensive Survey ◽  
Network Disruption ◽  
Open Issues

Vehicular networks are emerging as a promising technology that enables reliable and low-cost solutions for intelligent transport systems (ITSs), mainly due to their enormous potential to be considered for multiple purposes and scenarios. These networks are characterized by unique and challenging features such as packet fragmentation, low node density, short contact duration, and network disruption. These features may result in the absence of a path between the source and destination nodes, which is one of the most challenging issues faced by this type of network. To overcome some of these problems, it is necessary to provide vehicular networks with sophisticated tools or methodologies to implement monitoring and management operations. However, designing efficient solutions for this type of network is not an easy task due to its particular characteristics. This paper elaborates on a comprehensive survey focusing on promising proposals to deal with monitoring and management functionalities in vehicular networks. This work aims not only to present the state of the art on monitoring and management solutions but also to analyze their benefits and drawbacks, identify open issues, and provide guidelines for further contributions.

scholarly journals Internet of things in healthcare monitoring to enhance acquisition performance of respiratory disorder sensors

2019 ◽  
Vol 15 (5) ◽  
pp. 155014771984712 ◽  
Author(s):  
Leonardo Juan Ramírez López ◽  
Arturo Rodriguez Garcia ◽  
Gabriel Puerta Aponte
Keyword(s):  
Heart Rate ◽  
Internet Of Things ◽  
Oxygen Saturation ◽  
Low Cost ◽  
Respiratory Disorder ◽  
Sensors And Actuators ◽  
Efficient Performance ◽  
Proposed Model ◽  
Healthcare Monitoring ◽  
Mean Differences

The implementation of the Internet of things in healthcare is a promising challenge to achieve coverage for a bigger number of users in different places at lower costs. Internet of things might mean better technology regarding response time and proper control of medical parameters. This study introduces an Internet-of-things system for healthcare with possibilities to control medical variables according to recent breakthroughs in sensors and data processing. The goal of the system is to optimize the development of applications to obtain variables in real time and with less energy consumption. The proposed model is validated on the measurement and monitoring of oxygen saturation, heart rate, and body temperature in patients with respiratory disorders. This was achieved by the optimization of data acquisition, integrated into a secure architecture using Message Queuing Telemetry Transport protocol. A cloud architecture with interconnection to low-cost and open-source devices was implemented, which interconnect to the sensors and actuators’ network. The experimental results were statistically treated against the device pattern data, through hypothesis tests for mean differences to probe the accuracy of the model. Finally, the proposed model demonstrates an efficient performance in several clinical parameters, such as oxygen saturation and heart rate per minute.

scholarly journals Expert Advisor (EA) Evaluation System Using Web-based ELECTRE Method in Foreign Exchange (Forex) Market

2018 ◽  
Vol 31 ◽  
pp. 10001
Author(s):  
Satibi Satibi ◽  
Catur Edi Widodo ◽  
Farikhin Farikhin
Keyword(s):  
New York ◽  
Real Time ◽  
Evaluation System ◽  
Web Applications ◽  
Historical Data ◽  
Web Based ◽  
Testing Period ◽  
Trading Market ◽  
Electre Method ◽  
The Right

This research aims to optimize forex trading profit automatically using EA but its still keep considering accuracy and drawdown levels. The evaluation system will classify EA performance based on trading market sessions (Sydney, Tokyo, London and New York) to determine the right EA to be used in certain market sessions. This evaluation system is a web-based ELECTRE methods that interact in real-time with EA through web service and are able to present real-time charts performance dashboard using web socket protocol communications. Web applications are programmed using NodeJs. In the testing period, all EAs had been simulated 24 hours in all market sessions for three months, the best EA is valued by its profit, accuracy and drawdown criteria that calculated using web-based ELECTRE method. The ideas of this research are to compare the best EA on testing period with collaboration performances of each best classified EA by market sessions. This research uses three months historical data of EUR/USD as testing period and other 3 months as validation period. As a result, performance of collaboration four best EA classified by market sessions can increase profits percentage consistently in testing and validation periods and keep securing accuracy and drawdown levels.

scholarly journals Sustainable Irrigation System for Farming Supported by Machine Learning and Real-Time Sensor Data

Sensors ◽  
2021 ◽  
Vol 21 (9) ◽  
pp. 3079
Author(s):  
André Glória ◽  
João Cardoso ◽  
Pedro Sebastião
Keyword(s):  
Machine Learning ◽  
Random Forest ◽  
Real Time ◽  
New Technologies ◽  
Irrigation System ◽  
Low Cost ◽  
Time Of Day ◽  
Machine Learning Algorithms ◽  
Sensor Data ◽  
Sensors And Actuators

Presently, saving natural resources is increasingly a concern, and water scarcity is a fact that has been occurring in more areas of the globe. One of the main strategies used to counter this trend is the use of new technologies. On this topic, the Internet of Things has been highlighted, with these solutions being characterized by offering robustness and simplicity, while being low cost. This paper presents the study and development of an automatic irrigation control system for agricultural fields. The developed solution had a wireless sensors and actuators network, a mobile application that offers the user the capability of consulting not only the data collected in real time but also their history and also act in accordance with the data it analyses. To adapt the water management, Machine Learning algorithms were studied to predict the best time of day for water administration. Of the studied algorithms (Decision Trees, Random Forest, Neural Networks, and Support Vectors Machines) the one that obtained the best results was Random Forest, presenting an accuracy of 84.6%. Besides the ML solution, a method was also developed to calculate the amount of water needed to manage the fields under analysis. Through the implementation of the system it was possible to realize that the developed solution is effective and can achieve up to 60% of water savings.

Sign in / Sign up

Export Citation Format

Share Document