scholarly journals Vector Maps Mobile Application for Sustainable Eco-Driving Transportation Route Selection

2020 ◽  
Vol 12 (14) ◽  
pp. 5584
Author(s):  
Vahid Balali ◽  
Soheil Fathi ◽  
Mehrdad Aliasgari
Keyword(s):  
Decision Making ◽  
Real Time ◽  
Fuel Consumption ◽  
Mobile Application ◽  
Ghg Emissions ◽  
Transportation Systems ◽  
Route Selection ◽  
Travel Costs ◽  
Traffic Rate ◽  
Carbon Dioxide Co2

The decisions managing all modes of transportation are currently based on the traffic rate and travel time. However, other factors such as Green House Gas (GHG) emissions, the sustainability index, fuel consumption, and travel costs are not considered. Therefore, more comprehensive methods need to be implemented to improve transportation systems and support users’ decision making in their daily commute. This paper addresses current challenges by utilizing data analytics derived from our proposed mobile application. The proposed application quantifies various factors of each transportation mode including but not limited to the cost, trip duration, fuel consumption, and Carbon Dioxide (CO2) emissions. All calculated travel costs are based on the real-time gas prices and toll fees. The users are also able to navigate to their destination and update the total travel costs in real-time. The emissions data per trip basis are aggregated to provide analytics of emissions usage. The traffic data is collected for the Southern California region and the effectiveness of the application is evaluated by twenty participants from California State University, Long Beach. The results demonstrate the application’s impacts on users’ decision-making and the propriety of the factors used in route selection. The proposed application can foster urban planning and operations vis-à-vis daily commutes, and as a result improve the citizens’ quality of life in various aspects.

Implementation of IoT-Based Generator Management System Using GPy

2021 ◽  
Vol 10 (1) ◽  
pp. 33-49
Author(s):  
Deepak Sheshbadan Verma ◽  
Sumit Satish Pai ◽  
Krishna Nagendra Vishwakarma
Keyword(s):  
Real Time ◽  
Fuel Consumption ◽  
Mobile Application ◽  
Current Method ◽  
Diesel Generator ◽  
Current Management ◽  
Digital Devices ◽  
Ac Power ◽  
Modern Business ◽  
New System

In the era of digital devices, many industries still use traditional methods of pen and paper to maintain records. One such industry is the diesel generator industry where these generators are operated without any proper supervision. The current management of these generator vans is highly unorganized. This causes a lot of miscommunication between the owners and the customers. The idea focuses on monitoring the different parameters of a diesel generator using internet-connected sensors. Parameters such as fuel consumption, AC power ON time, RPM of the turbine, and temperature are measured in real time. The system helps the owners to monitor their generators vans through one mobile application rather than depending on the on-site operators. Both the owners and customers can see how much power was consumed and how their bill was generated. Rather than using pen and paper to maintain records in the current method, the new system completely transforms the old methods into a highly digitalized modern business.

scholarly journals Advancements in multi-objective eco-routing solutions using connectivity

2021 ◽  
Author(s):  
Lama Alfaseeh
Keyword(s):  
Real Time ◽  
Predictive Models ◽  
Short Term Memory ◽  
Ghg Emissions ◽  
Transportation Systems ◽  
Time Data ◽  
Distributed Routing ◽  
Multi Objective ◽  
Routing Strategy ◽  
The Impact

Due to the significant adverse impact of transportation systems on the environment, topics related to alleviating greenhouse gas (GHG) emissions are gaining more attention. As potential solutions to mitigate GHG emissions, several approaches have been proposed to better control traffic and manage transportation systems. The employment of Intelligent Transportation System (ITS), which adopts the advancements in Information and Communication Technology (ICT), has been proposed as the most favourable approach to alleviate the undesirable impact of transportation systems on the environment. ITS can control several aspects of a network, such as speed, traffic signals, and route guidance. For the purpose of routing, this research aims to exploit the advancements in ICT by including connected and automated vehicles (CAVs) and sensing technology in an urban congested network.<div>Anticipatory multi-objective eco-routing in a distributed routing framework was proposed and compared to myopic routing with a large case study on a congested network. The End-to-End Connected Autonomous Vehicles (E2ECAV) dynamic distributed routing framework was examined, and encouraging results were found based on the traffic and environmental perspectives. The impact of different market penetration rates (MPRs) of CAVs was examined for various traffic conditions. E2ECAV was adopted for both the myopic and anticipatory routing strategies in this dissertation. The best GHG costing approach was defined and was among the elements tackled in this research. For a robust anticipatory routing application, predictive models were developed based on Long-Short Term Memory (LSTM), a deep learning approach, while considering a high level of spatial (link level) and temporal (one minute) resolution. With regards to the LSTM predictive models, the impact was illustrated of using a deeper LSTM network and systematically tuning its hyper-parameters. The anticipatory routing strategy significantly outperformed the myopic routing strategy based on the the traffic and environmental perspectives. This research shows that ITS can help significantly reduce GHG emissions produced by transportation systems. The developed predictive models can be used while real-time data are collected from sensors within an urban network. Furthermore, the proposed anticipatory routing framework can be applied in a real-time situation. </div>

scholarly journals Evaluation of Greenhouse Gas Emissions from Municipal Solid Waste (MSW) Management: Case Study of Lampang Municipality, Thailand

2018 ◽  
pp. 46-56 ◽  
Author(s):  
Pantitcha Outapa ◽  
Veerapas Na Roi-et
Keyword(s):  
Municipal Solid Waste ◽  
Greenhouse Gas ◽  
Solid Waste ◽  
Fuel Consumption ◽  
Management Strategies ◽  
Ghg Emissions ◽  
Travel Distance ◽  
Emission Model ◽  
Msw Management ◽  
Carbon Dioxide Co2

The issue of greenhouse gas (GHG) emissions from municipal solid waste (MSW) is important in the context of climate change. Reduction of GHGs from waste disposal systems is one of the management strategies forming part of Thailand’s National Economic and Social Development Plan. This project evaluated emissions from a municipal solid waste system covering transportation and disposal in Lampang Municipality, northern Thailand. GHG emissions from transportation were estimated by the Institute for Global Environmental Strategies (IGES) based on the travel distance of the vehicles, using a vehicle emission model and vehicle fuel consumption. GHG emissions during the disposal process were also estimated based mainly on the model of IGES. The results indicated that GHG emissions from sanitary landfill were highly dominated by methane (CH4) emissions (20,346 tons CO2eq a-1). In addition, carbon dioxide (CO2) was emitted (226 tons a-1) from the transportation process. This evaluation found that GHG emission estimates based on travel distance were lower than those based on fuel consumption (44 %). Furthermore, changing from diesel fuel to compressed natural gas will reduce transportation emissions by approximately 7 %.

scholarly journals Driver Rating: a mobile application to evaluate driver behavior

2021 ◽  
Vol 2 (2) ◽  
pp. 1147-1160
Author(s):  
Nielson S. Trindade ◽  
Artur H. Kronbauer ◽  
Helder G. Aragão ◽  
Jorge Campos
Keyword(s):  
Carbon Dioxide ◽  
Urban Environment ◽  
Fuel Consumption ◽  
Intelligent Transportation Systems ◽  
Mobile Application ◽  
Driver Behavior ◽  
Carbon Dioxide Emission ◽  
Intelligent Transportation ◽  
Transportation Systems

The combination of data from sensors embedded in vehicles and smartphones promises to generate great innovations in intelligent transportation systems. This article presents Driver Rating, a mobile application to evaluate the behavior of drivers based on the data gathered from vehicles´ and smartphones´ sensors. The Driver Rating application analyzes five variables (fuel consumption, carbon dioxide emission, speed, longitudinal acceleration, and transverse acceleration) to evaluate driver´s behaviors while driving. To test the Driver Rating application and identify its potentialities, an experiment was carried out on an urban environment, showing promising results regarding the classification of drivers’ behavior.

scholarly journals Simulasi Aplikasi Real Time Route Selection berbasis Wireless Sensor Network di Kota Makassar

2020 ◽  
Vol 2 (2) ◽  
pp. 84-98
Author(s):  
Erick Alfons Lisangan ◽  
Sean Coonery Sumarta ◽  
Levi Oktavian Tandungan
Keyword(s):  
Decision Making ◽  
Fuzzy Logic ◽  
Wireless Sensor Network ◽  
Real Time ◽  
Sensor Network ◽  
Wireless Sensor ◽  
Multi Criteria Decision Making ◽  
Route Selection ◽  
Data Traffic ◽  
Traffic Condition

Seiring dengan pertumbuhan kota yang secara di dunia melebihi 50%, persoalan kota menjadi lebih rumit dan kompleks, salah satunya adalah kemacetan yang dapat disebabkan oleh banjir serta pertumbuhan kendaraan yang melebihi luas jalanan. Hal ini juga terjadi di Kota Makassar sebagai ibu kota provinsi Sulawesi Selatan. Saat ini sering terjadi kemacetan lalu lintas di beberapa ruas jalan di Kota Makassar, terutama pada saat peak hours. Data terakhir Juni 2017 menunjukkan jumlah kendaraan di kota Makassar adalah sebanyak 1.425.635 dimana terjadi kenaikan lebih dari 100% dibandingkan tahun 2007. Pada penelitian ini akan dirancang sebuah aplikasi real time route selection dengan memanfaatkan Wireless Sensor Network sebagai penyedia data traffic condition pada ruas jalan. Algoritma pencarian rute terpendek yang digunakan adalah algoritma Dijkstra serta algoritma Floyd-Warshall yang dikombinasikan dengan fungsi skalar Chebycheff. Hasil penelitian menunjukkan bahwa rute yang dihasilkan oleh kedua algoritma sama tetapi algoritma Dijkstra memiliki waktu pemrosesan lebih cepat dengan rerata 7,45 ms. Kelemahan fungsi skalar Chebycheff adalah proses update jarak antar node yang dinamis bergantung pada perubahan kondisi lalu lintas. Hal ini dapat diatasi dengan menggunakan penggunaan metode inferensi lain untuk kriteria kondisi lalu lintas, seperti fuzzy logic maupun metode Multi Criteria Decision Making.

scholarly journals Advancements in multi-objective eco-routing solutions using connectivity

2021 ◽  
Author(s):  
Lama Alfaseeh
Keyword(s):  
Real Time ◽  
Predictive Models ◽  
Short Term Memory ◽  
Ghg Emissions ◽  
Transportation Systems ◽  
Time Data ◽  
Distributed Routing ◽  
Multi Objective ◽  
Routing Strategy ◽  
The Impact

Due to the significant adverse impact of transportation systems on the environment, topics related to alleviating greenhouse gas (GHG) emissions are gaining more attention. As potential solutions to mitigate GHG emissions, several approaches have been proposed to better control traffic and manage transportation systems. The employment of Intelligent Transportation System (ITS), which adopts the advancements in Information and Communication Technology (ICT), has been proposed as the most favourable approach to alleviate the undesirable impact of transportation systems on the environment. ITS can control several aspects of a network, such as speed, traffic signals, and route guidance. For the purpose of routing, this research aims to exploit the advancements in ICT by including connected and automated vehicles (CAVs) and sensing technology in an urban congested network.<div>Anticipatory multi-objective eco-routing in a distributed routing framework was proposed and compared to myopic routing with a large case study on a congested network. The End-to-End Connected Autonomous Vehicles (E2ECAV) dynamic distributed routing framework was examined, and encouraging results were found based on the traffic and environmental perspectives. The impact of different market penetration rates (MPRs) of CAVs was examined for various traffic conditions. E2ECAV was adopted for both the myopic and anticipatory routing strategies in this dissertation. The best GHG costing approach was defined and was among the elements tackled in this research. For a robust anticipatory routing application, predictive models were developed based on Long-Short Term Memory (LSTM), a deep learning approach, while considering a high level of spatial (link level) and temporal (one minute) resolution. With regards to the LSTM predictive models, the impact was illustrated of using a deeper LSTM network and systematically tuning its hyper-parameters. The anticipatory routing strategy significantly outperformed the myopic routing strategy based on the the traffic and environmental perspectives. This research shows that ITS can help significantly reduce GHG emissions produced by transportation systems. The developed predictive models can be used while real-time data are collected from sensors within an urban network. Furthermore, the proposed anticipatory routing framework can be applied in a real-time situation. </div>

scholarly journals Evaluating the Impacts of Parking App Services on Travellers' Choice Behaviour and Traffic Dynamics

2020 ◽  
Vol 32 (2) ◽  
pp. 179-191
Author(s):  
Jingjing Liang ◽  
Xiaoning Zhang ◽  
Huang Yan
Keyword(s):  
Real Time ◽  
Intelligent Transportation Systems ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
Choice Behaviour ◽  
Traffic Dynamics ◽  
Travel Costs ◽  
Parking Lot ◽  
Parking Management ◽  
Management Policies

As the products of intelligent transportation systems, parking apps have become convenient platforms for implementing parking policies, which can be provided as parking app services. This paper proposes a traffic simulation model for evaluating the impacts of parking app services on the travellers’ choice behaviour and traffic dynamics. Travellers are assumed to use three types of parking app services: the provision of information on real-time parking lot occupancies, parking reservation, and the display of dynamic parking fees. The behaviour of travellers, such as travellers’ mode choices, departure time choices, and learning behaviour, are considered in this model. Numerical experiments show that providing information on real-time parking lot occupancies can be helpful in reducing the use ratio of commercial parking lots, but the effect will ultimately be smoothed during the evolution of traffic dynamics. Moreover, parking reservation is an effective way to reduce travel costs and encourage travellers to choose park-and-ride. Furthermore, dynamic parking fees usually lead to the oscillation of traffic dynamics and travellers’ choices, in addition to an increase in travel costs. This model is a useful tool for analysing the impacts of other parking management policies that can be implemented as parking app services and can be a reference for evaluating the impacts of other parking polices.

scholarly journals Enhancing Traffic Safety with Mobile Applications

2016 ◽  
Vol 9 (3) ◽  
pp. 216
Author(s):  
H Kaartinen ◽  
J Jämsä
Keyword(s):  
Decision Making ◽  
Real Time ◽  
Traffic Safety ◽  
Intelligent Transportation Systems ◽  
Mobile Applications ◽  
Data Transfer ◽  
Research Work ◽  
Transportation Systems ◽  
Point Of View ◽  
Time Data

Intelligent Transportation Systems (ITS) have great potential and market on modern traffic environment. Technologies of the day enable the real-time data transfer and presentation for the actors in traffic and outside of it. Inter-cognitive communication is a form of communication where an information system gathers data and processes it to a form of which users can benefit on their decision making. In this paper we will present how deploying new cognitive elements on mobile applications can increase traffic safety. The most important point of view in sharing the traffic data is how to present it for the driver and how to make the data transfer reliable and safe. New vehicles have built-in solutions, such as comprehensive infotainment systems, to present the information and warnings, but older vehicles do not have this option. Therefore the modern devices, such as smartphones and tablet computers can be utilized for these purposes. This paper describes Centria’s research work on developing mobile applications for improving the traffic flow and safety by real-time support for the driver’s decision making. Also, the data security has been studied and tested at Centria, and will be reported in this paper.

A Highly Efficient and Optimised Simulation Based Multi objective Decision-Making for FMS Control

2018 ◽  
Vol 6 (6) ◽  
pp. 98
Author(s):  
Shreyanshu Parhi ◽  
S. C. Srivastava
Keyword(s):  
Decision Making ◽  
Real Time ◽  
Manufacturing Industry ◽  
Simulation Software ◽  
Shop Floor ◽  
Simulation Tool ◽  
Routing Flexibility ◽  
Decision System ◽  
Multi Objective ◽  
Arena Simulation

Optimized and efficient decision-making systems is the burning topic of research in modern manufacturing industry. The aforesaid statement is validated by the fact that the limitations of traditional decision-making system compresses the length and breadth of multi-objective decision-system application in FMS.  The bright area of FMS with more complexity in control and reduced simpler configuration plays a vital role in decision-making domain. The decision-making process consists of various activities such as collection of data from shop floor; appealing the decision-making activity; evaluation of alternatives and finally execution of best decisions. While studying and identifying a suitable decision-making approach the key critical factors such as decision automation levels, routing flexibility levels and control strategies are also considered. This paper investigates the cordial relation between the system ideality and process response time with various prospective of decision-making approaches responsible for shop-floor control of FMS. These cases are implemented to a real-time FMS problem and it is solved using ARENA simulation tool. ARENA is a simulation software that is used to calculate the industrial problems by creating a virtual shop floor environment. This proposed topology is being validated in real time solution of FMS problems with and without implementation of decision system in ARENA simulation tool. The real-time FMS problem is considered under the case of full routing flexibility. Finally, the comparative analysis of the results is done graphically and conclusion is drawn.

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