Cargo Container Monitoring Data Reliability Evaluation in WSN Nodes

Jakovlev, Sergej; Andziulis, Arūnas; Bulbenkienė, Violeta; Didžiokas, Rimantas; Bogdevičius, Marijonas; Plestys, R.; Zakarevicius, R.A.

doi:10.5755/j01.eee.119.3.1371

Cited by 3 publications

(1 citation statement)

References 2 publications

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“…e system's primary goal is to monitor the real-time way and work of cargo conditions during transportation and evaluate the potential risks of cargo transportation, thereby providing mobile cargo security services. However, sensor-based container damage detection has data errors, mechanical damage, sensor system damage, and external environmental factors, which affect the credibility and accuracy of real-time decision-making [26]. In addition, due to differences in transportation requirements and environments for different goods, it is difficult to form a modular container detection standard based on sensor monitoring.…”

Section: Research On Cargo and Auxiliary Inspectionmentioning

confidence: 99%

Multitype Damage Detection of Container Using CNN Based on Transfer Learning

Wang

Gao

Zeng

et al. 2021

Mathematical Problems in Engineering

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Due to the repeated bearing of mechanical operations and natural factors, the container will suffer various types of damage during use. Adopting effective container damage detection methods plays a vital role in prolonging the service life and using function. This paper proposes a multitype damage detection model for containers based on transfer learning and MobileNetV2. In addition, a data set containing nine typical types of container damage is established. To ensure the validity and practicability of the model, we conducted tests and verifications in the actual port environment. The results show that the model can identify multiple types of container damage. Compared with the existing models, the damage detection model proposed in this paper can ensure the identification effect of various types of container damage, which is more suitable for the actual container detection situation. This method can provide a new idea of damage detection for container management in ports.

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Section: Research On Cargo and Auxiliary Inspectionmentioning

confidence: 99%