scholarly journals Moving Towards Intelligent Transportation via Artificial Intelligence and Internet-of-Things

Sensors ◽  
2020 ◽  
Vol 20 (23) ◽  
pp. 6945
Author(s):  
Miltiadis D. Lytras ◽  
Kwok Tai Chui ◽  
Ryan Wen Liu
Keyword(s):  
Artificial Intelligence ◽  
Internet Of Things ◽  
Smart City ◽  
Intelligent Transportation ◽  
Transport Networks ◽  
Smart Transportation

One of the key smart city visions is to bring smarter transport networks, specifically intelligent/smart transportation [...]

scholarly journals Artificial Intelligence Sebagai Penggerak Industri 4.0 dan Tantangannya Bagi Sektor Pemerintah dan Swasta

2019 ◽  
Vol 10 (1) ◽  
pp. 68
Author(s):  
Reza Yogaswara
Keyword(s):  
Neural Network ◽  
Artificial Intelligence ◽  
Big Data ◽  
Deep Learning ◽  
Internet Of Things ◽  
Competitive Advantage ◽  
Smart City ◽  
Chief Information Officer ◽  
Deep Learning Neural Network

Artificial Intelligence (AI) atau kecerdasan buatan menjadi penggerak revolusi industri 4.0 yang menjanjikan banyak kemudahan bagi sektor pemerintah maupun industri. Internet of Things (IoT) dan big data contohnya dimana AI dapat diimplementasikan, teknologi yang telah banyak diadopsi di era industri 4.0 ini mampu menghubungkan setiap perangkat, seseorang dapat mengotomatisasi semua perangkat tanpa harus berada di lokasi, lebih dari itu, saat ini telah banyak mesin yang dapat menginterprestasi suatu kondisi atau kejadian tertentu dengan bantuan AI, sebagaimana telah kamera cerdas pendeteksi kepadatan volume kendaraan di jalan raya menggunakan teknologi Deep Learning Neural Network, yang telah diimplementasikan pada beberapa Pemerintah Daerah Kabupaten dan Kota dalam mendukung program Smart City yang telah dicanangkan. Pada sektor industri, banyak juga dari mereka yang telah mengotomatisasi mesin produksi dan manufaktur menggunakan robot dan Artificial Intelligence, sehingga Industri 4.0 akan meningkatkan daya saing melalui perangkat cerdas, setiap entitas yang mampu menguasai teknologi ini disitulah keunggulan kompetitifnya (competitive advantage). Namun ditengah perkembangan industri 4.0 yang cukup masif pemerintah harus bergerak cepat dalam mengadopsi platform ini, jika tidak, mereka akan menurunkan efisiensi proses bisnis untuk menjaga stabilitas layanan publik. Oleh sebab itu diperlukan keilmuan dan pemahaman yang benar bagi pemerintah dalam menghadapai era Industri 4.0, dimana Chief Information Officer (CIO) dapat mengambil peranan penting dalam memberikan dukungan yang didasari atas keilmuan mereka terkait tren teknologi industri 4.0, khususnya AI yang telah banyak diadopsi di berbagai sektor.

scholarly journals A Survey on the Use-Cases and Deployment Efforts Toward Converged Internet of Things (IoT) and Vehicle-to-Everything (V2X) Environments

2021 ◽  
Author(s):  
Hamdan Hejazi ◽  
László Bokor
Keyword(s):  
Internet Of Things ◽  
Intelligent Transportation Systems ◽  
Smart City ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
Use Cases ◽  
Vehicular Communication ◽  
Internet Of Vehicles ◽  
The Past ◽  
Comprehensive Survey

In the past few years, automotive Internet of Things (IoT) solutions have become one of the most significant IoT application areas in the shape of vehicular communication to connect vehicles and such the so-called Internet of Vehicles (IoV) to be used in Intelligent Transportation Systems (ITS) environments. With an increasing level of cooperation, ITS could facilitate smart city operations by providing cooperative intelligent traffic solutions. Modern Cooperative ITS (C-ITS) solutions have started to be implemented in the whole world with various deployment models and significant improvements in the integration of Vehicle-to-Everything (V2X) communication and IoT solutions. To highlight the current V2X technology evolution towards an IoT/IoV era, this paper presents a comprehensive survey about the convergence between IoT and V2X use-cases together with their supporting technologies in the cooperative ITS ecosystem worldwide. We show how IoT could enable advanced V2X applications to get widespread and increase ITS efficiency.

Internet of Things Architecture for Intelligent Transportation Systems in a Smart City

2021 ◽  
Author(s):  
Majid Moazzami ◽  
Niloufar Sheini-Shahvand ◽  
Ersan Kabalci ◽  
Hossein Shahinzadeh ◽  
Yasin Kabalci ◽  
...  
Keyword(s):  
Internet Of Things ◽  
Intelligent Transportation Systems ◽  
Smart City ◽  
Intelligent Transportation ◽  
Transportation Systems

scholarly journals Artificial Intelligence-Based Semantic Internet of Things in a User-Centric Smart City

Sensors ◽  
2018 ◽  
Vol 18 (5) ◽  
pp. 1341 ◽  
Author(s):  
Kun Guo ◽  
Yueming Lu ◽  
Hui Gao ◽  
Ruohan Cao
Keyword(s):  
Artificial Intelligence ◽  
Internet Of Things ◽  
Smart City ◽  
User Centric

scholarly journals Convergence of Blockchain and IoT for Secure Transportation Systems in Smart Cities

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Khizar Abbas ◽  
Lo’Ai A. Tawalbeh ◽  
Ahsan Rafiq ◽  
Ammar Muthanna ◽  
Ibrahim A. Elgendy ◽  
...  
Keyword(s):  
Internet Of Things ◽  
Smart City ◽  
Smart Cities ◽  
Transportation System ◽  
Heterogeneous Data ◽  
Sensor Data ◽  
The Internet ◽  
Transit System ◽  
Smart Transportation ◽  
The Internet Of Things

Smart cities provide citizens with smart and advanced services to improve their quality of life. However, it has been observed that the collection, storage, processing, and analysis of heterogeneous data that are usually borne by citizens will bear certain difficulties. The development of the Internet of Things, cloud computing, social media, and other Industry 4.0 influencers pushed technology into a smart society’s framework, bringing potential vulnerabilities to sensor data, services, and smart city applications. These vulnerabilities lead to data security problems. We propose a decentralized data management system for smart and secure transportation that uses blockchain and the Internet of Things in a sustainable smart city environment to solve the data vulnerability problem. A smart transportation mobility system demands creating an interconnected transit system to ensure flexibility and efficiency. This article introduces prior knowledge and then provides a Hyperledger Fabric-based data architecture that supports a secure, trusted, smart transportation system. The simulation results show the balance between the blockchain mining time and the number of blocks created. We also use the average transaction delay evaluation model to evaluate the model and to test the proposed system’s performance. The system will address residents’ and authorities’ security challenges of the transportation system in smart, sustainable cities and lead to better governance.

scholarly journals Redefining smartness in township with Internet of Things & Artificial Intelligence: Dholera city

2020 ◽  
Vol 170 ◽  
pp. 06001
Author(s):  
Raghav Bang ◽  
Manish Patel ◽  
Vasu Garg ◽  
Vishal Kasa ◽  
Jyoti Malhotra ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Water Management ◽  
Internet Of Things ◽  
Waste Management ◽  
Smart City ◽  
Smart Grids ◽  
Carbon Dioxide Emissions ◽  
Smart Cities ◽  
Urban City ◽  
The City

Internet of Things (IoT) with Artificial Intelligence (AI) has the virtue to address the key challenges encountered by the excessive Urban population; contributing to water management, waste management, energy crisis, and many such affairs. The urban city has reached the level of water scarcity with no adequate water supply. The lack of interconnectivity within the city also leads to severe consequences, such as delayed responses to emergency situations along with irregular traffic and infrastructure management. “Dholera” the futuristic city attempt to solve these issues. Dholera is the biggest and India’s first upcoming greenfield smart city solution developed under the Delhi Mumbai Industrial Corridor (DMIC) project in Gujarat, India. We have analyzed a few domains from this township project, to mention a few - Water Management, Waste Management, City Integrated Operation Centre (CIOC) and City portal. This paper spotlights on the novel ideas enhancing the smart city features and the working. Automating the city resources using futuristic technologies like big data analytics, Artificial Intelligence (AI) and the Internet of Things (IoT) would make the city well-functioning. In Dholera city, various sensors are mounted and interconnected to collect the data, monitor it, and communicate the values for dynamic action(s). Dholera has AI-based urban transportation, smart grids, renewable energy, solar power, waste and water management, along with urban farming, contributing to a reduction in carbon dioxide emissions and improving energy, water and managing traffic issues effectively. Smart cities are well classified as the growth bar contributing to the universal economy. This paper presents various models making the Dholera city a Fast Responsive, Sustainable, Intelligent and well-connected township.

scholarly journals Analyzing the Adoption Challenges of the Internet of Things (IoT) and Artificial Intelligence (AI) for Smart Cities in China

2021 ◽  
Vol 13 (19) ◽  
pp. 10983
Author(s):  
Ke Wang ◽  
Yafei Zhao ◽  
Rajan Kumar Gangadhari ◽  
Zhixing Li
Keyword(s):  
Artificial Intelligence ◽  
Internet Of Things ◽  
Smart City ◽  
Water Distribution ◽  
Smart Cities ◽  
Vital Role ◽  
The Internet ◽  
Causal Relationships ◽  
City Development ◽  
The Internet Of Things

Smart cities play a vital role in the growth of a nation. In recent years, several countries have made huge investments in developing smart cities to offer sustainable living. However, there are some challenges to overcome in smart city development, such as traffic and transportation management, energy and water distribution and management, air quality and waste management monitoring, etc. The capabilities of the Internet of Things (IoT) and artificial intelligence (AI) can help to achieve some goals of smart cities, and there are proven examples from some cities like Singapore, Copenhagen, etc. However, the adoption of AI and the IoT in developing countries has some challenges. The analysis of challenges hindering the adoption of AI and the IoT are very limited. This study aims to fill this research gap by analyzing the causal relationships among the challenges in smart city development, and contains several parts that conclude the previous scholars’ work, as well as independent research and investigation, such as data collection and analysis based on DEMATEL. In this paper, we have reviewed the literature to extract key challenges for the adoption of AI and the IoT. These helped us to proceed with the investigation and analyze the adoption status. Therefore, using the PRISMA method, 10 challenges were identified from the literature review. Subsequently, determination of the causal inter-relationships among the key challenges based on expert opinions using DEMATEL is performed. This study explored the driving and dependent power of the challenges, and causal relationships between the barriers were established. The results of the study indicated that “lack of infrastructure (C1)”, ”insufficient funds (C2)”, “cybersecurity risks (C3)”, and “lack of trust in AI, IoT” are the causal factors that are slowing down the adoption of AI and IoT in smart city development. The inter-relationships between the various challenges are presented using a network relationship map, cause–effect diagram. The study’s findings can help regulatory bodies, policymakers, and researchers to make better decisions to overcome the challenges for developing sustainable smart cities.

Sign in / Sign up

Export Citation Format

Share Document