1 Introduction
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The design of parallel Internet of Vehicles for managing large-scale logistics transport vehicles is proposed. This system makes use of the ACP intelligent approach.
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A novel approach for extracting information on large-scale logistics transport vehicles is proposed using the Adaboost algorithm.
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An approach for position monitoring of large-scale logistics transport vehicles is proposed using the Tabu search method.
2 Related work
Authors | Approach | Is CPS used? | AI method used? | Efficiency | Accuracy | Storage space utilization |
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Alias et al. [9] | Image Processing based vehicle monitoring | ✖ | ✖ | \(\to\) | \(\to\) | \(\uparrow\) |
Xia et al. [10] | Tabu Search-based monitoring system | ✖ | ✖ | \(\to\) | \(\uparrow\) | \(\uparrow\) |
Husain et al. [11] | Video Processing based vehicle detection | ✖ | ✓ | \(\to\) | \(\to\) | \(\to\) |
Chen [12] | Logistics distribution optimization using Big data and cloud | ✖ | ✓ | \(\to\) | \(\to\) | \(\downarrow\) |
Yi and Ma [13] | Design of transportation monitoring and logistic protection | ✖ | ✓ | \(\to\) | \(\to\) | \(\to\) |
Zheng and Man [14] | Location routing for logistic management | ✓ | ✖ | \(\to\) | \(\to\) | \(\uparrow\) |
Qi [15] | Tracking and monitoring for logistics management on a multimedia platform | ✖ | ✓ | \(\to\) | \(\uparrow\) | \(\uparrow\) |
Abbasi et al. [16] | Survey on Intelligent transport system and vehicle detection | ✖ | ✓ | * | * | * |
Wang et al. [17] | Monitor vehicle safety using IoT | ✖ | ✖ | \(\to\) | \(\to\) | \(\uparrow\) |
Chinonso et al. [18] | IoT-based vehicle detection | ✖ | ✖ | \(\to\) | \(\to\) | \(\to\) |
Qimin et al. [19] | GPS vehicle monitoring system using WebGIS | ✖ | ✖ | \(\to\) | \(\to\) | \(\uparrow\) |
Liang | Proposed intelligent monitoring Methodology for large-scale logistics transport vehicles based on PIoV | ✓ | ✓ | \(\uparrow\) | \(\uparrow\) | \(\downarrow\) |
3 Intelligent monitoring approach of large-scale logistics transport vehicles
3.1 Design of parallel Internet of Vehicles
3.2 Extraction of large-scale transportation vehicle monitoring information
3.3 Position monitoring of large-scale logistics transport vehicles
3.3.1 Looking for a suitable filtering algorithm via Tabu Search
3.3.2 Important sampling and positioning
4 Experiment
4.1 Algorithm analysis of vehicle monitoring and locationing
5 Results and discussion
5.1 Analysis of vehicle monitoring information data extraction effects
Vehicle monitoring data volume/10,000 | The algorithm applied in this work | Vehicle monitoring algorithm based on motion estimation | WebGIS-based vehicle monitoring algorithm |
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200 | 1.35 | 5.61 | 7.12 |
400 | 1.32 | 5.15 | 5.14 |
600 | 1.36 | 5.23 | 4.89 |
800 | 1.28 | 4.89 | 7.46 |
1000 | 1.31 | 6.52 | 7.36 |
1200 | 1.34 | 6.23 | 4.99 |
1400 | 1.36 | 6.47 | 5.56 |
Vehicle monitoring data volume/10,000 | The algorithm applied in this paper | Vehicle monitoring algorithm based on motion estimation | WebGIS-based vehicle monitoring algorithm |
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200 | 2.1 | 4.2 | 8.8 |
400 | 1.8 | 4.0 | 12.3 |
600 | 1.9 | 6.1 | 8.4 |
800 | 1.4 | 8.9 | 7.6 |
1000 | 2.1 | 10.4 | 9.1 |
1200 | 2.2 | 4.6 | 9.5 |
1400 | 1.8 | 9.9 | 11.2 |