Proposing the systems to provide protection of vehicles against theft and accident

Das, Prasanta; Sengupta, Sharmila

doi:10.1109/rteict.2016.7808119

Cited by 7 publications

(7 citation statements)

References 7 publications

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“…Online perception of driving safety module: When the driving safety monitoring system is used [ 31 ], detectable objects (people, cats, dogs, etc.) enter the blind spot of the driver’s visual blind area.…”

Section: Online Real-time Perception and Evaluation Of Driving Visual...mentioning

confidence: 99%

Online Collaborative Perception of Full Bridge Deck Driving Visual of Far Blind Area on Suspension Bridge during Vortex-Induced Vibration

Dan,

Zeng,

2024

Sensors

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During a vertical vortex-induced vibration (VVIV), an undulating bridge deck will affect drivers’ sightlines, causing the phenomenon of drifting and changes in the far blind area, thus presenting a potential threat to driving safety. Consequently, to ensure the safety of driving on a suspension bridge deck under VVIV, it is necessary to perceive the far blind spot caused by the occlusion of the driving sightlines under this condition, and to establish an online perception and evaluation mechanism for driving safety. With a long-span suspension bridge experiencing VVIV as the engineering background, this paper utilizes the acceleration integration algorithm and the sine function fitting method to achieve the online perception of real-time dynamic configurations of the main girder. Then, based on the configurations, the maximum height of the driver’s far blind area and effective sight distance are calculated accordingly, and the impact of different driving conditions on them is discussed. The proposed technical framework for driving safety perception in far blind spots is feasible, as it can achieve real-time estimation of the maximum height and effective distance of the far blind area, thereby providing technical support for bridge–vehicle–human collaborative perception and traffic control during vortex-induced vibration.

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Section: Online Real-time Perception and Evaluation Of Driving Visual...mentioning

confidence: 99%

Online Collaborative Perception of Full Bridge Deck Driving Visual of Far Blind Area on Suspension Bridge during Vortex-Induced Vibration

Dan,

Zeng,

2024

Sensors

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“…The driver must obey traffic laws, and be able to predict the dangers that may arise in the blind area based on the characteristics of the blind area of their vehicle and drive accurately. These are too challenging for fatigued and elderly drivers [ 5 , 7 , 34 ], so developing an online data processing system is necessary to ensure driving safety during VVIV.…”

Section: Online Real-time Perception Of Front Blind Area During Vviv ...mentioning

confidence: 99%

“…Following this, the intersection between the sightline and the dynamic configuration is determined, and the front blind spot is calculated. The module for monitoring driving safety in real time: In the environment where the driving safety monitoring system is utilized [ 34 ], the detected objects (person, dog, cat, etc.) enter the driver’s blind area.…”

Section: Online Real-time Perception Of Front Blind Area During Vviv ...mentioning

confidence: 99%

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Online Intelligent Perception of Front Blind Area of Vehicles on a Full Bridge Based on Dynamic Configuration Monitoring of Main Girders

Zeng

Dan

Guan

et al. 2022

Sensors

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Establishing an online perception mechanism for a driver’s front blind area on a full bridge under vertical vortex-induced vibration (VVIV) is essential for ensuring road safety and traffic control on bridge decks under specific conditions. Based on accelerations of vibration monitoring of the main girders, this paper uses a real-time acceleration integration algorithm to obtain real-time displacements of measurement points; realizes the real-time estimation of the dynamic configurations of a main girder through parametric function fitting; and then can perceive the front blind area for vehicles driving on bridges experiencing VVIV in real time. On this basis, taking a long-span suspension bridge suffering from VVIV as an engineering example, the influence of different driving conditions on the front blind area is examined. Then, the applicability of the intelligent perception technology framework of the front blind area is verified. The results indicate that, during VVIV, the driver’s front blind area changes periodically and the vehicle model has the most significant impact on the front blind area; in contrast, the vehicle’s speed and the times of the vehicle entering the bridge have minimal impact on it. Meanwhile, it is shown that the framework can accurately perceive front blind areas of vehicles driving on the bridge, and identify different vehicle models, speeds and times of vehicle bridge entries in real time.

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“…These techniques are applied either on thermal or visual imaging data, and they require a dedicated imaging device, i.e., a camera which mounted on the vehicle. This technique loses its appeal in low to medium income countries, where the vehicle riders are more concerned about the device's theft [15] than personal safety. Considering the practicality of ML and CV based pothole detection schemes, they are often trained on limited sampled datasets, e.g., < 200 in [11]; thus, the reported high level of accuracy of their trained classifiers may not be achieved in a real-world situation.…”

Section: Introductionmentioning

confidence: 99%

SmartPPM: An Internet of Things Based Smart Helmet Design for Potholes and Air Pollution Monitoring

Singh

Chandna²,

Upadhyay

2019

EAI Endorsed Trans IoT

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In a country with an extensive road network, it is very tough for authorities to identify and repair the potholes on time, which emerge due to casual wear and tear of the road. These potholes are dangerous for unsuspecting high-speed vehicles and results in multiple life-threatening accidents year-round. Apart from potholes, another severe concern about the time spent on roads is air pollution. Breathing the polluted air, mainly containing the particulate matter that has a diameter of fewer than 2.5 micrometers, is toxic to humans. In this work, we have judiciously designed an Internet of Things based smart helmet, which uses crowdsourcing to report potholes and collect crucial on-road air pollution data so that a person could avoid risk to life and health. We have also introduced the novel concept of remembrance factor and severity index, which could be useful in dealing with the stale and invalid pothole data in the database.

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Proposing the systems to provide protection of vehicles against theft and accident

Cited by 7 publications

References 7 publications

Online Collaborative Perception of Full Bridge Deck Driving Visual of Far Blind Area on Suspension Bridge during Vortex-Induced Vibration

Online Collaborative Perception of Full Bridge Deck Driving Visual of Far Blind Area on Suspension Bridge during Vortex-Induced Vibration

Online Intelligent Perception of Front Blind Area of Vehicles on a Full Bridge Based on Dynamic Configuration Monitoring of Main Girders

SmartPPM: An Internet of Things Based Smart Helmet Design for Potholes and Air Pollution Monitoring

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