A novel IoT platform for the era of connected cars

Marosi, Attila Csaba; Lovas, Róbert; Kisari, Ádám; Simonyi, E.

doi:10.1109/fiot.2018.8325597

Cited by 20 publications

(6 citation statements)

References 5 publications

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“…The role of connectivity in extending automotive perception capabilities is, however, outside the scope of this article; the reader is referred to [190] and [191]. Connectivity also enables updates and, thus, improvements in ML models while offering new perception-driven services [192], [193]. However, it also brings additional challenges, such as transformation errors between the different reference frames, delays, and uncertainty with respect to the shared information, security, and trust, which need to be addressed.…”

Section: Future Outlookmentioning

confidence: 99%

Sensing and Machine Learning for Automotive Perception: A Review

et al. 2023

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Automotive perception involves understanding the external driving environment and the internal state of the vehicle cabin and occupants using sensor data. It is critical to achieving high levels of safety and autonomy in driving. This article provides an overview of different sensor modalities, such as cameras, radars, and light detection and ranging (LiDAR) used commonly for perception, along with the associated data processing techniques. Critical aspects of perception are considered, such as architectures for processing data from single or multiple sensor modalities, sensor data processing algorithms and the role of machine learning techniques, methodologies for validating the performance of perception systems, and safety. The technical challenges for each aspect are analyzed, emphasizing machine learning approaches, given their potential impact on improving perception. Finally, future research opportunities in automotive perception for their wider deployment are outlined.

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Section: Future Outlookmentioning

confidence: 99%

Sensing and Machine Learning for Automotive Perception: A Review

et al. 2023

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“…This has resulted in a growing interest in studying vehicle sensor data from a big data perspective. Attila et al [20] proposed an Internet-of-Things platform for connected cars that aims to process sensor data by introducing cloud computing and big data processing technologies. They reliably collected and processed data from multiple sensors.…”

Section: Collecting Storing and Processing Vehicle Sensor Datamentioning

confidence: 99%

Lane-Level Map Generation and Management Framework Using Connected Car Data

Kim,

Moon,

Moon

2023

Electronics

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This study proposes a lane-level map generation and management framework using connected sensor data to reduce the manpower and time required for producing and updating high-definition (HD) maps. Unlike previous studies that relied on the onboard processing capabilities of vehicles to collect map-constructing elements, this study offloads computing for map generation to the cloud, assigning vehicles solely the role of transmitting sensor data. For efficient data collection, we divide the space into a grid format to define it as a partial map and establish the state of each map and its transition conditions. Lastly, tailored to the characteristics of the road elements composing the map, we propose an automated map generation technique and method for selectively collecting data. The map generation method was tested using data collected from actual vehicles. By transmitting images with an average size of 350 KB, implementation was feasible even with the current 5G upload bandwidth. By utilizing 12,545 elements, we were able to achieve a position accuracy and regression RMSE of less than 0.25 m, obtaining 651 map elements to construct the map. We anticipate that this study will help reduce the manpower and time needed for deploying and updating HD maps.

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“…Cars may be connected [18] in a variety of ways, a simple navigation system [19] being one of the first examples of connectivity. Today, there are cars that connect to the internet using a SIM card, and applications [20] that require fast communication are being designed to use the benefits of the 5G [21,22] and IoT technology [23,24], creating an internet of vehicles digital space [25,26]. There are also other ways and protocols [27] that cars use to communicate between them, such as through blockchain secured ad-hoc vehicle networks [28,29] and LiFi communication [30,31].…”

Section: Connected Cars and Smart Transport Infrastructurementioning

confidence: 99%

Ubiquitous Computing: Driving in the Intelligent Environment

et al. 2021

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In the context of hyper-connected cars and a growing heterogeneous digital ecosystem, we wish to make the most of the data available from the various sensors, devices and services that compose the ecosystem, in order to propose a proof of concept in-vehicle system that enhances the driving experience. We focus on improving the driving experience along three main directions, namely: (1) driving and trip planning, (2) health and well-being and (3) social and online activities. We approached the in-vehicle space as a smart interface to the intelligent driving environment. The digital data-producers in the ecosystem of the connected car are sources of raw data of various categories, such as data from the outside world, gathered from sensors or online services, data from the car itself and data from the driver gathered with various mobile and wearable devices, by means of observing his state and by means of his social media and online activity. Data is later processed into three information categories—driving, wellness, and social—and used to provide multi-modal interaction, namely visual, audio and gesture. The system is implemented to act in response to the trafficked information on different levels of autonomy, either in a reactive manner, by simple monitoring, or in a proactive manner. The system is designed to provide an in-vehicle system that assists the driver with planning the travel (Drive panel), by providing a comfortable environment for the driver while monitoring him (Wellness panel), and by adaptively managing interactions with their phone and the digital environment (Social panel). Heuristic evaluation of the system is performed, with respect to guidelines formulated for automated vehicles, and a SWOT analysis of the system is also presented in the paper.

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A novel IoT platform for the era of connected cars

Cited by 20 publications

References 5 publications

Sensing and Machine Learning for Automotive Perception: A Review

Sensing and Machine Learning for Automotive Perception: A Review

Lane-Level Map Generation and Management Framework Using Connected Car Data

Ubiquitous Computing: Driving in the Intelligent Environment

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