Conceptual Design of Smart Network Adaptive Traffic Light in Creating Low-Carbon City

The research led to the development of a smart sensory network adaptive traffic light to optimise traffic flow and reduce congestion on Jalan Persisiran Seri Alam in Pasir Gudang. This system, with variable time management, can reduce the time spent at traffic junctions and the carbon emitted by vehicles, thus supporting the SDG 11 for low carbon smart city. By integrating the dynamic duration of each traffic signal on each dense pathway, this system can help reduce traffic congestion, fuel consumption, and CO2 emissions. It can also ensure that traffic is managed in a more efficient manner, thus improving the quality of life for the people of Pasir Gudang. The success of this system will be a major step towards achieving the goal of a low carbon smart city, as it will help to reduce air pollution, noise pollution and improve road safety. Additionally, it can help to improve the efficiency of traffic flow, leading to better traffic management and reduced congestion

Conceptual Design of Smart Network Adaptive Traffic Light in Creating Low-Carbon City

The research led to the development of a smart sensory network adaptive traffic light to optimise traffic flow and reduce congestion on Jalan Persisiran Seri Alam in Pasir Gudang. This system, with variable time management, can reduce the time spent at traffic junctions and the carbon emitted by vehicles, thus supporting the SDG 11 for low carbon smart city. By integrating the dynamic duration of each traffic signal on each dense pathway, this system can help reduce traffic congestion, fuel consumption, and CO2 emissions. It can also ensure that traffic is managed in a more efficient manner, thus improving the quality of life for the people of Pasir Gudang. The success of this system will be a major step towards achieving the goal of a low carbon smart city, as it will help to reduce air pollution, noise pollution and improve road safety. Additionally, it can help to improve the efficiency of traffic flow, leading to better traffic management and reduced congestion

Mobile Application to support fuel-efficient driving through situation awareness

Abstract. Situation awareness is usually conceptualized as design and implementation principles for safety critical industries like aviation or military. Finland was one of the first countries in the world to establish an intelligent transport systems (ITS) strategy in 2009. Increasing the situation awareness in traffic is regarded as one of the means to implement the strategy. In the theoretical part of this thesis, we explore the use of situation awareness and context awareness in intelligent transport systems. Particularly, the thesis focuses on summarizing proper design and evaluation principles to provide situation awareness support for fuel efficient driving. These guidelines were exploited in implementing a mobile application, called Driving Coach Mobile Application in the practical part of the thesis. The purpose of the application is to provide awareness to the drivers about how they can save fuel. Driving Coach Mobile Application’s accordance of design and implementation principles to situation awareness support is validated by user study with simulated data focused on usability, usefulness and fuel efficiency awareness support. The results of this thesis can be used in fleet management planning, city planning as well as in personal driving, for example.Tilannetietoinen mobiilisovellus polttoainetaloudellisen ajamisen tueksi. Tiivistelmä. Turvallisuuskriittisissä teollisuuden osa-alueissa kuten ilmailussa tai sotilaallisessa toiminnassa, eri toimijoiden tilannetietoisuuden parantamiseen tähtäävät suunnittelu- sekä toteutusperiaatteet ovat olleet merkittävässä roolissa jo pitkään. Suomi oli maailman ensimmäisiä maita, jotka julkistivat älykkään liikenteen strategian jo vuonna 2009. Tilannetietoisuuden parantaminen liikenteessä on edelleen eräs tämän strategian toimeenpanomuoto. Tämän työn teoreettisessa osassa tutkitaan avulla tilannetietoisuuden sekä toimintatilanteesta tietoisuuden soveltamista älyliikenteessä. Erityisesti tarkastellaan suunnittelu- sekä evaluointiperiaatteita polttoainetalouden tehokkuuden lisäämiselle tilannetietoisuuden avulla. Työn käytännön osuudessa sovellettiin näitä periaatteita mobiilisovelluksen toteuttamiseksi. Mobiilisovellus tukee kuljettajien polttoainetehokkaampaa ajamista. Sovellus testattiin käytettävyyden, hyödyllisyyden sekä polttoainetehokkaan ajamisen tuen suhteen. Sovellusta voidaan käyttää esimerkiksi kaupunkisuunnittelussa, autokannan toiminnan tarkkailemisessa tai vaikka henkilökohtaisen ajotavan arvioinnissa

RITThe Contributions of Traffic Management Centers in life Enhancement

This study focuses on investigating the contributions of traffic management centers to enhancing people’s driving experiences and impacting their level of satisfaction and happiness. Data was collected in the United Arab Emirates through two distinct surveys; the first aimed at drivers (number of respondents: 155), and the second aimed at traffic management center operators (number of respondents: 15). The drivers survey aimed to collect data about drivers’ pain points experienced while driving in the United Arab Emirates and showed that slow drivers on fast lanes and sudden lane changing are the biggest challenges reported. On the operators’ side, the data collected showed that operators reported observing these challenges from their side as well. Operators also notably reported the need for advanced technology to help better manage and respond to real time traffic situations remotely from traffic management centers. Both surveys conducted showed a need and potential for the contributions of traffic management centers in enhancing and upgrading the quality of life for citizens through the application of technological solutions and the development of supporting legislation. Supplementary data from similar surveys was also used to validate, expand the knowledge and provide a holistic view of the topic. The study indicated that traffic management centers can impact the happiness and satisfaction of citizens by enhancing their driving experience, given that they are designed and equipped in a way that suits the city and society trends and cultures. Recommendations for implementation of such design choices were given along five pillars considering administration (based on best practice and Benchmarking), technology (results of local and international TMC surveys), media and communication (international survey and the expansion of technology and social media), operations and legislation (Based on results of the driver’s survey, that shows some gaps in the legislations which can be enhanced)

A Comparative and Analytical Review of Iot-Enabled Smart Accidental Management Systems

One of the most important issues that emerging nations are addressing is road accidents. It is important to develop smart accidental management systems with low cost and efforts to prevent accidents and causalities. The amalgamation of Intelligent Transportation Systems (ITS) and Information and Communications Technology (ICT) is expected to dramatically change how people experience driving by enabling cutting-edge traffic monitoring and incident detection strategies. This analysis focuses on various components of SAMS, such as sensor networks, communication protocols, data processing techniques, and decision-making algorithms. It examines how these components work together to create a connected infrastructure capable of detecting and responding to accidents promptly. The review highlights the role of data analytics in enhancing accident prediction and prevention. By processing and analyzing enormous real-time data from cameras, sensors, and other sources, IoT-driven SAMS can identify patterns and anomalies, allowing for proactive measures to avoid accidents in various settings, including transportation, industries, and public spaces

Smart and Secure Blockchain Structure to Track Vehicle Record-keeping in the Sultanate of Oman

In the country of Sultanate of Oman, the Royal Oman Police (ROP) is responsible for carrying out the Inspection, Registration/Renewal, Transfer of ownership, Licensing of a vehicle and the Investigation of traffic accidents. The traditional system used for storing this information does not guarantee whether any information has been tampered with or manipulated. Having a tamper-proof methodology like Blockchain to capture this important information in a distributed ledger register can enable all the participants in the Registration Chain (Supplier of the vehicle, Owner of the vehicle, various Government Agencies and public at large) to gain confidence, build trust and authenticate records that are maintained by the centralised agency. In this paper, a groundbreaking solution built on Hyperledger Besu, a permissioned Ethereum blockchain platform, is introduced that offers a revolutionary approach to vehicle registration and management. It ensures secure and immutable vehicle registration, utilizing IPFS for document storage and ERC-20 tokens to track vehicle history. This Ethereum-powered system facilitates transparent ownership transfers, comprehensive vehicle history tracking, streamlined insurance renewals, seamless vehicle inspections, real-time tracking, and blockchain-based verification, all contributing to heightened efficiency and trust in vehicle processes for the Omani government. By integrating blockchain technology, this solution addresses the challenges of data integrity, security, and transparency that have long plagued the vehicle registration and transfer processes in Oman. This paper highlights the potential of blockchain to revolutionize governmental services and improve the overall efficiency and trustworthiness of vehicle-related transactions, ultimately benefiting both the government and citizens alike

Vehicle Localization Kalman Filtering for Traffic Light Advisor Application in Urban Scenarios

The recent advancements in Intelligent Transportation Systems (ITS) have revealed significant potential for enhancing traffic management through Advanced Driver Assist Systems (ADASs), with benefits for both safety and environment. This research paper proposes a vehicle localization technique based on Kalman filtering, as accurate positioning of the ego-vehicle is essential for the proper functioning of the Traffic Light Advisor (TLA) system. The aim of the TLA is to calculate the most suitable speed to safely reach and pass the first traffic light in front of the vehicle and subsequently keep that velocity constant to overcome the following traffic light, thus allowing safer and more efficient driving practices, thereby reducing safety risks, and minimizing energy consumption. To overcome Global Positioning Systems (GPS) limitations encountered in urban scenarios, a multi-rate sensor fusion approach based on the Kalman filter with map matching and a simple kinematic one-dimensional model is proposed. The experimental results demonstrate an estimation error below 0.5 m on urban roads with GPS signal loss areas, making it suitable for TLA application. The experimental validation of the Traffic Light Advisor system confirmed the expected benefits with a 40% decrease in energy consumption compared to unassisted driving

Analysis of Smart Parking System Using IOT Environment

The typical parking experience has been transformed by smart parking systems that use the Internet of Things (IoT) environment to integrate technology to improve efficiency, convenience, and sustainability. In order to monitor and manage parking spaces in real-time, this unique technique makes use of IoT devices, such as sensors, cameras, and networking technologies. As a result of the system's reliable information on parking availability, drivers may find and book parking spaces in advance, which eases traffic and reduces aggravation. Additionally, parking systems with IoT capabilities optimize resource use, lowering carbon emissions and fostering sustainability. The adoption of IoT in parking systems is a crucial step towards building smarter, more connected cities that will enhance both drivers' and parking operators' experiences with parking. There are numerous crucial elements in the process for developing a smart parking system in an IoT context. First, sensors are placed in parking places to gather up-to-the-minute occupancy information. Then, using wireless communication protocols, this data is sent to a central server or cloud computing platform. After that, a data processing and analysis module interprets the gathered data using algorithms and machine learning techniques and presents parking availability information to users via a mobile application or other user interfaces. For effective management and monitoring of parking spaces, the system also includes automated payment methods and interacts with existing infrastructure. Taken as Alternative parameters is Park Smart, Street line, Park Whiz, ParkMobile, Spot Hero. Taken as evaluation parameters is Light Sensor, CCTV coins, SMS, Cost-effectiveness, Timestamp. This demonstrates the rank of the data set Park Smart is on 1st Rank, ParkMobile is on 2nd Rank, Park Whiz is on 3rd Rank, Street line is on 4th Rank and Spot Hero is on 5th Rank. To sum up, implementing a smart parking system employing IoT technology has shown to be a potential way to deal with the problems associated with urban parking. The system increases parking efficiency, lessens traffic congestion, and enhances user experience by utilising IoT sensors, data analytics, and real-time communication. The parking scene in smart cities has the potential to change dramatically, enhancing ease and sustainability