Cyber physical system for vehicle counting and emission monitoring

Khan, Ali Mehmood; Khattak, Khurram S.; Khan, Zahoor; Khan, Mushtaq Ahmad; Minallah, Nasru

doi:10.19101/ijacr.2020.1048096

Cited by 6 publications

(11 citation statements)

References 14 publications

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“…In the existing literature, different compute boards such as Arduino Uno\Nano\ Mega [1,6,9,14], and Raspberry Pi [4,6] have been employed for sensor node development. However, for low-cost sensor node development, deciding factors for choosing a compute board range from cost (monetary and power consumption), computation requirement and design complexity.…”

Section: A Sensor Nodementioning

confidence: 99%

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Low-Cost Civil Structure Health Monitoring Using Wireless Sensor Network

Wiqar

Khattak

Malik

et al. 2023

PakJET

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This research presents a low-cost, real-time, reliable, and scalable solution for Structural Health Monitoring.(SHM) using an IoT-based multi-node system. The study's objective is to detect and identify damages timely andweaknesses in civil structures such as bridges, buildings, and dams, which environmental factors, overuse, or natural phenomena may cause. Each sensor node, fabricated using NodeMCU, is equipped with sensors for measuring vibration, shock, tilt, strain, humidity, and temperature. The data collected by multiple sensor nodes is transmitted to Amazon Web Services (AWS) cloud platform via Wi-Fi and analyzed for damage detection and predictive maintenance. The field testing on a pedestrian steel bridge showed over 99% success in data transmission with a frequency of 1 second per reading, resulting in 18,000 readings over 5 hours. With a fabrication cost of $40 per sensor node and scalable AWS resources, the proposed solution is highly scalable and can operate for 15 days without human intervention.

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Section: A Sensor Nodementioning

confidence: 99%

“…In this context, the AWS cloud platform has been employed for this work. AWS has a data upload capability of per second instead of 15 seconds for ThingSpeak [14,16]. Among the plethora of services offered by AWS, for this work, AWS lambda and DynamoDB have been used.…”

Section: Cloud Platformmentioning

confidence: 99%

Low-Cost Civil Structure Health Monitoring Using Wireless Sensor Network

Wiqar

Khattak

Malik

et al. 2023

PakJET

View full text Add to dashboard Cite

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“…However, compute vision-based edge computing solutions are limited because of resourceconstrained embedded computing boards. These proposed solutions can measure at most two traffic flow parameters, either count\classification or count\speed [14].…”

Section: A Research Contextmentioning

confidence: 99%

Vehicular Flow Characterization: An Internet of Video Things-Based Solution

Zakhil

Khan

Khattak

et al. 2023

PakJET

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Intelligent transportation systems (ITS) have emerged as the optimal solution to address urban mobility challenges. However, to effectively implement ITS, detailed traffic flow statistics are imperative. Various solutions have been proposed, including intrusive/non-intrusive sensors and compute vision-based solutions. However, these solutions have limitations in the number of measured traffic flow parameters, cost or performance under different traffic conditions. To overcome these limitations, we propose an Internet-of-Video-Things (IoVT) based solution. The sensor node (fabricated using Raspberry Pi Zero W, Pi camera, power bank, and Wi-Fi device) can live-streaming roadside traffic video to a remote Dell server located at our lab with Camlytics (commercially available traffic analysis software) installed. The proposed solution was field tested with a 45-minute live-streamed video of 720p at 25 frames per second. Results show that the proposed solution can measure more traffic flow parameters than intrusive and non-intrusive sensors, with an accuracy of 84.3% for vehicle count and speed estimation. Other parameters were also calculated, such as time/distance headway, spatial/temporal densities, heat maps, and trajectories. Additionally, the proposed solution can count pedestrians with an accuracy of 76.3%.

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“…(By 2027, it will be worth $7.8 trillion. Similarly, according to the United Nations (UN), the world's population has risen significantly from 751 million in 1950 to an expected 7.87 billion in 2021, with around 55 percent of the people living in metropolitan areas as of 2018 [1]. Because of these changes in the transportation sector, it has faced a lot of problems such as road congestion, accidents, and harmful emissions from the vehicles.…”

Section: Introductionmentioning

confidence: 99%

Efficient and Cost-Effective Aws Cloud-Based Solution for Traffic Videos Analysis

2022

IRJMETS

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Different research are underway, to make urbanite's life good, with the help of technology. Providing solutions to different urbanite problems such as traffic characterization, traffic congestion, identifying road accidents, and vehicle classification. The current solution offered in ITS involves two types of solution either streaming of traffic video to cloud for its computation or using edge device to compute. We made an alternate solution for the same purpose on the AWS cloud and trained our own YOLO model. The recorded video of the traffic was sent to AWS cloud for classification of vehicles. We got a detailed summary of video analysis using our trained model, its implementation using AWS in our proposed solution. The proposed model successfully classifies 1200 vehicles into 7 types in a 3 hour long video for which it was trained with a pretty good accuracy.

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Cyber physical system for vehicle counting and emission monitoring

Cited by 6 publications

References 14 publications

Low-Cost Civil Structure Health Monitoring Using Wireless Sensor Network

Low-Cost Civil Structure Health Monitoring Using Wireless Sensor Network

Vehicular Flow Characterization: An Internet of Video Things-Based Solution

Efficient and Cost-Effective Aws Cloud-Based Solution for Traffic Videos Analysis

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