Impacts of IoT and big data to automotive industry

Aris, Ishak; Sahbusdin, Ratna Kalos Zakiah; Amin, A.

doi:10.1109/ascc.2015.7244878

Cited by 21 publications

(7 citation statements)

References 6 publications

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“…Environmental monitoring and transportation networks are two areas where the Internet of Things finds use. This is particularly true in the automotive industry, which is home to some of the most significant inventions [9]. Here are some of the biggest ways the IoT is transforming the automotive industry and our roads…”

Section: Ways Iot Is Transforming Transportation Managementmentioning

confidence: 99%

Excavation of the Internet of Things in Urban Areas Based on an Intelligent Transportation Management System

Nambajemariya¹,

Wang²

2021

AIT

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Transportation, as one of the most common aspects people use in their daily lives, has resulted in highly complex traffic in urban areas due to the large number of private vehicles. As some results of the traffic congestion, there is energy consumption, environmental pollution, unplanned accidents, and time is wasted due to congestion and traffic jams. With the aid of the Internet of Things (IoT), which is an excellent computerized technology solution for all field claims, Internet of Things (IoT) technology has recently provided an efficient and effective traffic management system, especially in transportation, due to the combined functions IoT can handle, there are management, monitoring, tracking, identifying, computing, and so on. This article provided a comprehensive overview of a variety of intelligent management systems that have been built using IoT to alleviate traffic congestion.

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Section: Ways Iot Is Transforming Transportation Managementmentioning

confidence: 99%

Excavation of the Internet of Things in Urban Areas Based on an Intelligent Transportation Management System

Nambajemariya¹,

Wang²

2021

AIT

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“…The authors performed a comparative study and the results exhibited, SVM model can better solve the car evaluation, in turn, and the technique can be stretched to other industries to resolve the assessment of the product. In 2015, Bin Aris et al [9] emphasized the role played by Big Data and IoT in the automotive industry. The latest progression in technologies such as cloud computing, wireless distributed sensors, smart cognitive radio networks, embedded system, lightweight material, intelligent converter, highperformance battery, higher efficiency, ultra-low emission internal combustion engines, and fuel cell technology have become the talk of the town.…”

Section: State Of Artmentioning

confidence: 99%

Execution of Structured and Unstructured Mining in Automotive Industry Using Hortonworks Sandbox

Singh

Jagdev

2021

SN COMPUT. SCI.

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The market landscape has undergone dramatic change because of globalization, shifting marketing conditions, cost pressure, increased competition, and volatility. Transforming the operation of businesses has been possible because of the astonishing speed at which technology has witnessed the change. The automotive industry is on the edge of a revolution. The increased customer expectations, changing ownership, self-driving vehicles, and much more have led to the transformation of automobiles, applications, and services from artificial intelligence, sensors, RFID to big data analysis. Large automobile industries have been emphasizing the collection of data to gain insight into customer's expectations, preferences, and budgets alongside competitor's policies. Statistical methods can be applied to historical data, which has been gathered from various authentic sources and can be used to identify the impact of fixed and variable marketing investments and support automakers to come up with a more effective, precise, and efficient approach to target customers. Proper analysis of supply chain data can disclose the weak links in the chain enabling the adoption of timely countermeasures to minimize the adverse effects. To fully gain benefit from analytics, the collaboration of a detailed set of capabilities responsible for intersecting and integrating with multiple functions and teams across the business is required. The effective role played by big data analysis in the automobile industry has also been expanded in the research paper. The research paper discusses the scope and challenges of big data. The paper also elaborates on the working technology behind the concept of big data. The paper illustrates the working of MapReduce technology that executes in the back end and is responsible for performing data mining.

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“…Some aspects of the visualization of the extraction and relevant information that still need to be explored are based on the clustering insights of the data employed. Despite the fact that many studies employ big data analytics techniques [6]- [17], there are currently few studies in the Indonesian automobile sector that relate to new information or new patterns from existing sales data using data mining. An investigation of these issues is important because it can increase the effectiveness and efficiency of decision-making in the automotive industry.…”

Section: Introductionmentioning

confidence: 99%

“…Big data is also employed in autonomous cars to validate control and perception algorithms [16]. Furthermore, the integration of big data and the Internet of Things (IoT) is being utilized to hasten the process of developing energy efficient and intelligent vehicles (EEIV) to combat global warming, food security, and the depletion of nonrenewable energy resources [17].…”

Section: Introductionmentioning

confidence: 99%

Data Mining Modeling in Clustering Car Products Sales Data in the Automotive Industry in Indonesia

Astuti,

Yuniarti

2023

j. manaj. ind. dan logist.

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The research aims to build a model based on sales data for all automotive products in Indonesia using data mining with a k-means approach. This study uses automotive product sales data from January 2017 to September 2022. The lowest Davis-Bouldin index shows that three clusters (k=3) have the best performance. Based on the clustering results, 92% of the items are in cluster 0, 1% in cluster 1, and 7% in cluster 2. In addition, the clustering results show that cluster 1 is a car product with high sales volume. Cluster 2 is a car product with medium sales volume. Furthermore, cluster 0 is a car product with low sales volume. Business people or related parties can use data visualization and extraction from clustering results to learn the latest insights and information in determining business strategies, policies, and decisions to improve business competitiveness.

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Impacts of IoT and big data to automotive industry

Cited by 21 publications

References 6 publications

Excavation of the Internet of Things in Urban Areas Based on an Intelligent Transportation Management System

Excavation of the Internet of Things in Urban Areas Based on an Intelligent Transportation Management System

Execution of Structured and Unstructured Mining in Automotive Industry Using Hortonworks Sandbox

Data Mining Modeling in Clustering Car Products Sales Data in the Automotive Industry in Indonesia

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