scholarly journals Automatic Movable Smart Road Dividers - IOT Based Solution to Traffic Congestion Problems

2020 ◽  
Vol 5 (6) ◽  
pp. 1511-1516
Author(s):  
Keerthan A J ◽  
Likhith H D ◽  
Chetan H S ◽  
Kiran K P ◽  
Dr. Sumaiya MN
Keyword(s):  
Internet Of Things ◽  
Traffic Congestion ◽  
The Other ◽  
Traffic Density ◽  
Time Loss ◽  
Congestion Problems ◽  
Driving Conditions ◽  
The Web

The street dividers are commonly utilized for separating the street for continuous and approaching traffic. This is useful in keeping the progression of traffic. For this situation, there is equal number of lanes for both approaching and continuous traffic. Be that as it may, in certain zones, such as in industrial or shopping zones the traffic for the most part streams a one way in the first part of the morning or night. The other roadside is unfilled or unused. It leads to time loss for public and congested driving conditions. We mean to assemble a shrewd street divider as far as a mechanized street divider which moves or move the path coordinating the surge in rush hour gridlock. Such kind of component of traffic framework spares time as well as fuel. It can include 1 more path based the traffic in the specific bearing. With the more intelligent application planned underneath, manual reliance and manual traffic relation is decreased. Like this a proposition of savvy traffic is worked in less, medium and more density in the rush hour gridlock will be appeared in IOT server in utilizing grap diagram. IoT refers to Internet of Things where real digitalization comes into the image. The sensors and Arduino boards are utilized. The sensors are placed on the dividers which sense the progression of traffic and it is refreshed to the web through Wi-Fi module associated. The traffic density will be appeared in IoT server in utilizing graph chart. It gives a superior answer to traffic issue.

scholarly journals IMPLEMENTASI PENERAPAN INTERNET of THINGS(IoT)PADA MONITORING INFUS MENGGUNAKAN ESP 8266 DAN WEB UNTUK BERBAGI DATA

2017 ◽  
Vol 2 (1) ◽  
pp. 90-98 ◽  
Author(s):  
Dani Sasmoko ◽  
Yanuar Arief Wicaksono
Keyword(s):  
Internet Of Things ◽  
Intravenous Infusion ◽  
Physical Object ◽  
Medical Data ◽  
The Other ◽  
The Internet ◽  
Outpatient Services ◽  
Load Sensor ◽  
The Web ◽  
Made In

The delivery of medical data is of utmost importance to the successful treatment of patients. Efforts have been made in implementing technology both in outpatient services as well as hospital treatments for patients. Internet of things (IoT) is a concept that aims to transmit inherrent data from a physical object through the internet, therefore enabling the receiver on the other end to monitor, process and eventually make decisions based on this data. In this research, the physical object is an intravenous infusion bottle. An ESP 8266 module is connected to a load sensor to measure the volume of the bottle and sends the data via the internet. THe monitoring of the bottle volume can then be done in real time and with precision, without having the nurse manually check the volume or relying on family members to alert the nurse station. The monitoring of the bottle volume has been successfuly done with measurements recorded on a MySQL database and accessible through the web.

Effect of Polymer, Road Surface, and Driving Conditions on Wear Surface Characteristics of Tire Treads

1973 ◽  
Vol 1 (4) ◽  
pp. 354-362 ◽  
Author(s):  
F. R. Martin ◽  
P. H. Biddison
Keyword(s):  
Wear Surface ◽  
Surface Characteristics ◽  
Road Surface ◽  
The Other ◽  
Mechanical Degradation ◽  
Textured Surface ◽  
Test Track ◽  
Driving Conditions ◽  
Styrene Butadiene ◽  
Cylindrical Particles

Abstract Treads made with emulsion styrene-butadiene copolymer (SBR), solution SBR, polybutadiene (BR), and a 60/40 emulsion SBR/BR mixture were built as four-way tread sections on G78-15 belted bias tires, which were driven over both concrete and gravel-textured highways and on a small, circular, concrete test track. The tires were front mounted. When driven on concrete highway, all except the BR tread had either crumbled- or liquid-appearing surfaces, thought to have been formed by mechanical degradation or fatigue. When cornered on concrete, these materials formed small cylindrical particles or rolls. The BR tread had a smooth, granular-textured surface when driven on concrete highway and a ridge or sawtooth abrasion pattern when cornered on concrete. All the materials appeared rough and torn when run on gravel-textured highway. The differences in wear surface formed on BR tread and the other three are thought to be due primarily to the relatively high resilience of BR.

Determination of Optimal Public Transportation Routes Using Firefly and Tabu Search Algorithms

2020 ◽  
Vol 4 (5) ◽  
pp. 884-891
Author(s):  
Salwa Salsabila Mansur ◽  
Sri Widowati ◽  
Mahmud Imrona
Keyword(s):  
Tabu Search ◽  
Public Transportation ◽  
Traffic Congestion ◽  
Search Algorithm ◽  
Urban Transportation ◽  
The Public ◽  
Comparison Results ◽  
Congestion Problems ◽  
Transportation Routes

Traffic congestion problems generally caused by the increasing use of private vehicles and public transportations. In order to overcome the situation, the optimization of public transportation’s route is required particularly the urban transportation. In this research, the performance analysis of Firefly and Tabu Search algorithm is conducted to optimize eleven public transportation’s routes in Bandung. This optimization aims to increase the dispersion of public transportation’s route by expanding the scope of route that are crossed by public transportation so that it can reach the entire Bandung city and increase the driver’s income by providing the passengers easier access to public transportations in order to get to their destinations. The optimal route is represented by the route with most roads and highest number of incomes. In this research, the comparison results between the reference route and the public transportation’s optimized route increasing the dispersion of public transportation’s route to 60,58% and increasing the driver’s income to 20,03%.

scholarly journals Next Generation of SDN in Cloud-Fog for 5G and Beyond-Enabled Applications: Opportunities and Challenges

Network ◽  
2021 ◽  
Vol 1 (1) ◽  
pp. 28-49
Author(s):  
Ehsan Ahvar ◽  
Shohreh Ahvar ◽  
Syed Mohsan Raza ◽  
Jose Manuel Sanchez Vilchez ◽  
Gyu Myoung Lee
Keyword(s):  
Internet Of Things ◽  
Data Sharing ◽  
Mobile Networks ◽  
The Other ◽  
The Internet ◽  
Hybrid Cloud ◽  
Next Generation ◽  
Delay Constraints ◽  
Mission Critical ◽  
Iot Devices

In recent years, the number of objects connected to the internet have significantly increased. Increasing the number of connected devices to the internet is transforming today’s Internet of Things (IoT) into massive IoT of the future. It is predicted that, in a few years, a high communication and computation capacity will be required to meet the demands of massive IoT devices and applications requiring data sharing and processing. 5G and beyond mobile networks are expected to fulfill a part of these requirements by providing a data rate of up to terabits per second. It will be a key enabler to support massive IoT and emerging mission critical applications with strict delay constraints. On the other hand, the next generation of software-defined networking (SDN) with emerging cloudrelated technologies (e.g., fog and edge computing) can play an important role in supporting and implementing the above-mentioned applications. This paper sets out the potential opportunities and important challenges that must be addressed in considering options for using SDN in hybrid cloud-fog systems to support 5G and beyond-enabled applications.

Effect of Changing a Traffic Control Device Color on Driver Behavior and Perception across Different Age Groups

2021 ◽  
pp. 036119812110111
Author(s):  
Hatem Abou-Senna ◽  
Mohamed El-Agroudy ◽  
Mustapha Mouloua ◽  
Essam Radwan
Keyword(s):  
Traffic Control ◽  
Traffic Management ◽  
Driving Simulator ◽  
Age Groups ◽  
The United States ◽  
Time Of Day ◽  
General Purpose ◽  
Traffic Density ◽  
Driving Conditions ◽  
And Performance

The use of express lanes (ELs) in freeway traffic management has seen increasing popularity throughout the United States, particularly in Florida. These lanes aim at making the most efficient transportation system management and operations tool to provide a more reliable trip. An important component of ELs is the channelizing devices used to delineate the separation between the ELs and the general-purpose lane. With the upcoming changes to the FHWA Manual on Uniform Traffic Control Devices, this study provided an opportunity to recommend changes affecting safety and efficiency on a nationwide level. It was important to understand the impacts on driver perception and performance in response to the color of the EL delineators. It was also valuable to understand the differences between demographics in responding to delineator colors under different driving conditions. The driving simulator was used to test the responses of several demographic groups to changes in marker color and driving conditions. Furthermore, participants were tested for several factors relevant to driving performance including visual and subjective responses to the changes in colors and driving conditions. Impacts on driver perception were observed via eye-tracking technology with changes to time of day, visibility, traffic density, roadway surface type, and, crucially, color of the delineating devices. The analyses concluded that white was the optimal and most significant color for notice of delineators across the majority of subjective and performance measures, followed by yellow, with black being the least desirable.

Elite football teams that do not have a winter break lose on average 303 player-days more per season to injuries than those teams that do: a comparison among 35 professional European teams

2018 ◽  
Vol 53 (19) ◽  
pp. 1231-1235 ◽  
Author(s):  
Jan Ekstrand ◽  
Armin Spreco ◽  
Michael Davison
Keyword(s):  
Linear Regression ◽  
The Other ◽  
Climatic Region ◽  
Time Loss ◽  
Severe Injuries ◽  
Injury Rates ◽  
Level Data ◽  
Injury Burden ◽  
Or Team ◽  
Individual Training

ObjectiveTo compare injury rates among professional men’s football teams that have a winter break in their league season schedule with corresponding rates in teams that do not.Methods56 football teams from 15 European countries were prospectively followed for seven seasons (2010/2011–2016/2017)—a total of 155 team-seasons. Individual training, match exposure and time-loss injuries were registered. Four different injury rates were analysed over four periods within the season, and linear regression was performed on team-level data to analyse the effect of winter break on each of the injury rates. Crude analyses and analyses adjusted for climatic region were performed.Results9660 injuries were reported during 1 447 011 exposure hours. English teams had no winter break scheduled in the season calendar: the other European teams had a mean winter break scheduled for 10.0 days. Teams without a winter break lost on average 303 days more per season due to injuries than teams with a winter break during the whole season (p<0.001). The results were similar across the three periods August–December (p=0.013), January–March (p<0.001) and April–May (p=0.050). Teams without a winter break also had a higher incidence of severe injuries than teams with a winter break during the whole season (2.1 severe injuries more per season for teams without a winter break, p=0.002), as well as during the period January–March (p=0.003). A winter break was not associated with higher team training attendance or team match availability. Climatic region was also associated with injury rates.ConclusionsThe absence of a scheduled winter break was associated with a higher injury burden, both before and during the two periods following the time that many European teams take a winter break. Teams without a winter break (English clubs) had a higher incidence of severe injuries following the time of the year that other teams (other European clubs) had their scheduled break.

scholarly journals Applications of Internet of Things

2018 ◽  
Vol 7 (9) ◽  
pp. 334
Author(s):  
Chi-Hua Chen ◽  
Kuen-Rong Lo
Keyword(s):  
Internet Of Things ◽  
Intelligent Transportation Systems ◽  
Traffic Congestion ◽  
Location Privacy ◽  
High Efficiency ◽  
Transportation Systems ◽  
Location Based Services ◽  
Vehicle Operation ◽  
Vehicle Positioning ◽  
Coverage Estimation

This editorial introduces the special issue entitled “Applications of Internet of Things”, of ISPRS International Journal of Geo-Information. Topics covered in this issue include three main parts: (I) intelligent transportation systems (ITS), (II) location-based services (LBS), and (III) sensing techniques and applications. Three papers on ITS are as follows: (1) “Vehicle positioning and speed estimation based on cellular network signals for urban roads,” by Lai and Kuo; (2) “A method for traffic congestion clustering judgment based on grey relational analysis,” by Zhang et al.; and (3) “Smartphone-based pedestrian’s avoidance behavior recognition towards opportunistic road anomaly detection,” by Ishikawa and Fujinami. Three papers on LBS are as follows: (1) “A high-efficiency method of mobile positioning based on commercial vehicle operation data,” by Chen et al.; (2) “Efficient location privacy-preserving k-anonymity method based on the credible chain,” by Wang et al.; and (3) “Proximity-based asynchronous messaging platform for location-based Internet of things service,” by gon Jo et al. Two papers on sensing techniques and applications are as follows: (1) “Detection of electronic anklet wearers’ groupings throughout telematics monitoring,” by Machado et al.; and (2) “Camera coverage estimation based on multistage grid subdivision,” by Wang et al.

Improvement of the visual warning system for various driving and road conditions in road transportation

2017 ◽  
Vol 232 (2) ◽  
pp. 175-187 ◽  
Author(s):  
Güray Tonguç ◽  
İsmail Hakkı Akçay ◽  
Habib Gürbüz
Keyword(s):  
Warning System ◽  
Weather Conditions ◽  
The Other ◽  
Accelerometer Data ◽  
Road Transportation ◽  
Accelerometer Sensor ◽  
The Road ◽  
Information Displays ◽  
Driving Conditions ◽  
Vehicle Information

This study aims to identify the potential adverse driving conditions which result from driver behavior, road surfaces and weather conditions for vehicles during a cruise, and to inform the drivers of the other vehicles moving on the same route. Adverse driving condition scenarios were developed via acceleration data in lateral, longitudinal and vertical directions gathered by using an accelerometer sensor placed at the gravity center of the test vehicles. The drivers were warned through the symbols designed according to the developed scenarios in different shapes and colors, displayed on an information screen showing the position of the vehicle. Three different software programs were used for gathering and evaluating the accelerometer data, storing scenario-specific symbols on the internet and transferring these symbols to the other vehicle information displays. The road tests were performed in conditions present in Turkey. It was observed that the vehicle drivers were alerted with the warning symbols which were designed for dangerous road and driving conditions with a latency of approximately 6s on Google maps which appeared on the driver information screen.

scholarly journals A Hybrid Optimized LSTM Models for Human Activity Recognition with IOT Devices

2021 ◽  
pp. 182-189
Author(s):  
S. Arokiaraj ◽  
Dr. N. Viswanathan
Keyword(s):  
Deep Learning ◽  
Internet Of Things ◽  
Short Term Memory ◽  
The Other ◽  
Learning Models ◽  
Computational Overhead ◽  
Temporal Features ◽  
Human Movements ◽  
Proposed Model ◽  
Iot Devices

With the advent of Internet of things(IoT),HA (HA) recognition has contributed the more application in health care in terms of diagnosis and Clinical process. These devices must be aware of human movements to provide better aid in the clinical applications as well as user’s daily activity.Also , In addition to machine and deep learning algorithms, HA recognition systems has significantly improved in terms of high accurate recognition. However, the most of the existing models designed needs improvisation in terms of accuracy and computational overhead. In this research paper, we proposed a BAT optimized Long Short term Memory (BAT-LSTM) for an effective recognition of human activities using real time IoT systems. The data are collected by implanting the Internet of things) devices invasively. Then, proposed BAT-LSTM is deployed to extract the temporal features which are then used for classification to HA. Nearly 10,0000 dataset were collected and used for evaluating the proposed model. For the validation of proposed framework, accuracy, precision, recall, specificity and F1-score parameters are chosen and comparison is done with the other state-of-art deep learning models. The finding shows the proposed model outperforms the other learning models and finds its suitability for the HA recognition.

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