Low‐cost triboelectric sensor for speed measurement and weight estimation of vehicles

Yadav, Deepshikha; Azad, Puneet

doi:10.1049/iet-its.2018.5187

Cited by 20 publications

(5 citation statements)

References 23 publications

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“…Besides the diversified application scenarios mentioned earlier, TENGs also stand out to be attractive candidates for intelligent transportation systems. [ 351,352 ] They can be integrated into vehicles or roads to provide real‐time monitoring of humans, [ 353–357 ] vehicles, [ 358–362 ] and roads, [ 363,364 ] which can promote the accomplishment of the cooperative vehicle infrastructure system. For instance, TENGs have been reported to be integrated with nonmotorized vehicles (e.g., bicycles) as the auxiliary power source of low‐power electronics or self‐powered sensors.…”

Section: Tengs Enabled Applications In Different Fields Of Green Earthmentioning

confidence: 99%

Triboelectric Nanogenerator Enabled Wearable Sensors and Electronics for Sustainable Internet of Things Integrated Green Earth

Yang

Guo

Zhu

et al. 2022

Advanced Energy Materials

123

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as the components of the IoT network, and they will generate massive data with multidimensions, higher velocity, and improved heterogeneity. [2] Benefiting from this, our world is developing toward a smarter and more well-knit green earth, covering essential blocks like smart homes, smart agriculture, smart cities, smart industries as well as outer space and airlines. [3] In the green earth, the IoT systems are promising to be spread in every smart area, consisting of various sensing modules, signal processing modules, power management modules, power supply modules, etc. Sensing modules are applied to collect abundant information from the target objects or environment, such as temperature, humidity, light intensity, gas concentration, pressure, etc. And the signal processing modules help with the data transmission, processing, and analysis to connect and exchange information with other devices or systems to provide an optimal command to the target object or environment. In addition, the power management modules and power supply modules are to provide the most efficient solutions to reduce the overall power consumption in the operations of the IoT systems. [4][5][6] Thus, looking at the whole earth, it is to be closely connected with the IoT systems, enabling information transfer and communication over the strong network.Narrowing down to a single object like the human body, a single animal, or a robot, wearable electronics have attracted increasing research interest owing to their promising applications in real-time and precious monitoring and tracking of user's preferences and habits on the green earth. [7][8][9][10] Conventional wearable electronics involve smart watches, smart glasses, smart helmets, etc., while most of them are fabricated from nonflexible or rigid materials, resulting in limited wearable comfort, device lifetime, latency response, and loss of sensing information. [11][12][13] To address these issues, the current research focuses on the investigation of sensing materials with flexibility or even stretchability, breathability, washability, lightweight, adhesiveness, etc., enabling improved wearing comfort and long-term wearability. [14][15][16][17] Besides the wearability of the modules in the IoT system, energy issue is within wide research interest and concern as one of the urgent issues contemporarily. Batteries, as the dominant choices for power supply modules, are now revealed asThe advancement of the Internet of Things/5G infrastructure requires a lowcost ubiquitous sensory network to realize an autonomous system for information collection and processing, aiming at diversified applications ranging from healthcare, smart home, industry 4.0 to environmental monitoring. The triboelectric nanogenerator (TENG) is considered the most promising technology due to its self-powered, cost-effective, and highly customizable advantages. Through the use of wearable electronic devices, advanced TENG technology is developed as a core technology enabling self-powered sensors, power supplies, and data comm...

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Section: Tengs Enabled Applications In Different Fields Of Green Earthmentioning

confidence: 99%

Triboelectric Nanogenerator Enabled Wearable Sensors and Electronics for Sustainable Internet of Things Integrated Green Earth

Yang

Guo

Zhu

et al. 2022

Advanced Energy Materials

123

View full text Add to dashboard Cite

show abstract

“…A sensor node for traffic monitoring made of a combination of polytetrafluoroethylene (PTFE) and aluminium film deployed across the road was presented by Yadav et al [ 3 ]. In that solution, a well-known triboelectric effect was utilized to generate voltage spikes owing to frictional contact among two materials.…”

Section: Related Workmentioning

confidence: 99%

“…Information obtained by ITSs is necessary to provide various services that enable smoother, safer, and environmentally friendly transportation. Scientists have investigated various vehicle detection methods, ranging from inductive loops, piezo/quartz, and air switches/road tubes to various magnetometers, microwave radars, passive infrareds, ultrasonic, and video surveillance systems [ 1 , 2 , 3 ].…”

Section: Introductionmentioning

confidence: 99%

Analysis of Methods for Long Vehicles Speed Estimation Using Anisotropic Magneto-Resistive (AMR) Sensors and Reference Piezoelectric Sensor

Markevičius

Navikas

Miklusis

et al. 2020

Sensors

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With rapidly increasing traffic occupancy, intelligent transportation systems (ITSs) are a vital feature for urban areas. This paper analyses methods for estimating long (L > 10 m) vehicle speed and length using a self-developed system, equipped with two anisotropic magneto-resistive (AMR) sensors, and introduces a method for verifying the results. A well-known cross-correlation method of magnetic signatures is not appropriate for calculating the vehicle speed of long vehicles owing to limited resources and a long calculation time. Therefore, the adaptive signature cropping algorithm was developed and used with a difference quotient of a magnetic signature. An additional piezoelectric polyvinylidene fluoride (PVDF) sensor and video camera provide ground truth to evaluate the performances. The prototype system was installed on the urban road and tested under various traffic and weather conditions. The accuracy of results was evaluated by calculating the mean absolute percentage error (MAPE) for different methods and vehicle speed groups. The experimental result with a self-obtained data set of 600 unique entities shows that the average speed MAPE error of our proposed method is lower than 3% for vehicle speed in a range between 40 and 100 km/h.

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“…Moreover, some methods to determine the minimum number of sensors for path travel time full-observability been proposed in a few studies [13][14]. There some researchers have discussed the optimal number and locations of AVI sensors considering the trade-off between the estimation benefit and the cost [15][16][17][18]. However, the spatial resolution of these deployment methods of sensors may not be suitable for link travel time estimation.…”

Section: Introductionmentioning

confidence: 99%

Optimal number and locations of automatic vehicle identification sensors considering link travel time estimation

Zhu

Zhang

2023

IET Intelligent Trans Sys

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The problem of optimally locating Automatic Vehicle Identification (AVI) sensors on a traffic network for travel time estimation has been a topic of growing interests in recent years. Even though great progresses have been made on AVI sensor deployment for path‐level travel time estimation, very few contributions exist in the literatures that address the AVI sensor deployment for link‐level travel time estimation on an urban network. In this paper, considering the link travel time estimation, two deployment sub‐problems are addressed: (1) where to deploy a certain number of AVI sensors? (2) What is a cost‐effective number of AVI sensors to deploy? To address the first problem, a potential game of sensors is developed to find their optimal locations which maximize the objective function that consists of estimation coverage and estimation accuracy. Then, based on the optimal locations, an incremental search method is proposed to find the optimal number of sensors considering the cost. The case in Shanghai shows the proposed game‐theoretic method is superior to other two heuristic algorithms. Moreover, compared to the real‐world sensor locations, the optimally redeployed locations improve both the estimation coverage and estimation accuracy. The case in Xuancheng City validates the proposed incremental search uses less computations to find an optimal number that close to the global optimal number solved from the brute‐force search.

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Low‐cost triboelectric sensor for speed measurement and weight estimation of vehicles

Cited by 20 publications

References 23 publications

Triboelectric Nanogenerator Enabled Wearable Sensors and Electronics for Sustainable Internet of Things Integrated Green Earth

Triboelectric Nanogenerator Enabled Wearable Sensors and Electronics for Sustainable Internet of Things Integrated Green Earth

Analysis of Methods for Long Vehicles Speed Estimation Using Anisotropic Magneto-Resistive (AMR) Sensors and Reference Piezoelectric Sensor

Optimal number and locations of automatic vehicle identification sensors considering link travel time estimation

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