From the scope and technical system perspective, this paper sums up the history and current situation of logistics tracking and monitoring standards under international standards and national standards system. Taking ...From the scope and technical system perspective, this paper sums up the history and current situation of logistics tracking and monitoring standards under international standards and national standards system. Taking the first international standard developed by China in the field of logistics and Internet of Things as an example, it analyzes the status quo and trend of monitoring in logistics, presenting valuable experience for standards development in logistics tracking and monitoring in China.展开更多
[Objective] The paper is to construct the logistics tracking management system of tropical agricultural products based on supply chain.[Method] With tropical agricultural products in Hainan as study object,based on lo...[Objective] The paper is to construct the logistics tracking management system of tropical agricultural products based on supply chain.[Method] With tropical agricultural products in Hainan as study object,based on logistics supply chain files and electronic tag coding of agricultural products,cold chain temperature and humidity monitoring,vehicle transportation positioning,data exchange of XML Web services and role-based permission dynamic allocation,the multi-level multi-permission and multi-role logistics tracking management system of tropical agricultural products has been established.[Result] The system constructs information exchange platform for various links of logistics supply chain of tropical agricultural products,which realizes the entire quality monitoring and information tracing of agricultural products,thus enhancing the competitiveness of supply chain in company.[Conclusion] The system has good application and extension prospect.展开更多
Tyre pressure monitoring system(TPMS)is compulsory in most countries like the United States and European Union.The existing systems depend on pressure sensors strapped on the tyre or on wheel speed sensor data.A diffe...Tyre pressure monitoring system(TPMS)is compulsory in most countries like the United States and European Union.The existing systems depend on pressure sensors strapped on the tyre or on wheel speed sensor data.A difference in wheel speed would trigger an alarm based on the algorithm implemented.In this paper,machine learning approach is proposed as a new method to monitor tyre pressure by extracting the vertical vibrations from a wheel hub of a moving vehicle using an accelerometer.The obtained signals will be used to compute through statistical features and histogram features for the feature extraction process.The LMT(Logistic Model Tree)was used as the classifier and attained a classification accuracy of 92.5%with 10-fold cross validation for statistical features and 90.5% with 10-fold cross validation for histogram features.The proposed model can be used for monitoring the automobile tyre pressure successfully.展开更多
According to the development trend of intelligent logistics in our country, combining database, communication, GIS （Geography lnfolrnation System） technology, the paper study the key core technology of each module m...According to the development trend of intelligent logistics in our country, combining database, communication, GIS （Geography lnfolrnation System） technology, the paper study the key core technology of each module monitoring platform for vehicle monitoring system, and establish logistics transport vehicle monitoring platform that oriented small and medium-sized logistics enterprises, to realize the whole process of real-time monitoring for logistics and transport the vehicle from the warehouse to transportation, promote the informationization of logistics and transport.展开更多
The study of the logistics system mode based on the city construction is mainly according to the concrete characteristics of the logistics operation, to sum up the characteristics of the logistics system in the area o...The study of the logistics system mode based on the city construction is mainly according to the concrete characteristics of the logistics operation, to sum up the characteristics of the logistics system in the area of the set of the logistics information system, which aims to design a reasonable response model fi＇amework of the logistics system. This research is mainly based on the research on the GPS system, and deepening the logistics information system is to design and construct the function combination of the countermeasures of the logistics information technology, which is to design a complete system framework of the working state, hi addition to the related GIS technology, and the implementation of the monitoring and the control of the logistics information system, and the implementation of the navigation guidance in a reasonable range, provide the reference for the conslraction plan of the whole system, which lays a theoretical foundation for the healthy and effective operation of the countermeasures of the logistics information technology展开更多
This paper focuses on ozone prediction in the atmosphere using a machine learning approach. We utilize air pollutant and meteorological variable datasets from the El Paso area to classify ozone levels as high or low. ...This paper focuses on ozone prediction in the atmosphere using a machine learning approach. We utilize air pollutant and meteorological variable datasets from the El Paso area to classify ozone levels as high or low. The LR and ANN algorithms are employed to train the datasets. The models demonstrate a remarkably high classification accuracy of 89.3% in predicting ozone levels on a given day. Evaluation metrics reveal that both the ANN and LR models exhibit accuracies of 89.3% and 88.4%, respectively. Additionally, the AUC values for both models are comparable, with the ANN achieving 95.4% and the LR obtaining 95.2%. The lower the cross-entropy loss (log loss), the higher the model’s accuracy or performance. Our ANN model yields a log loss of 3.74, while the LR model shows a log loss of 6.03. The prediction time for the ANN model is approximately 0.00 seconds, whereas the LR model takes 0.02 seconds. Our odds ratio analysis indicates that features such as “Solar radiation”, “Std. Dev. Wind Direction”, “outdoor temperature”, “dew point temperature”, and “PM10” contribute to high ozone levels in El Paso, Texas. Based on metrics such as accuracy, error rate, log loss, and prediction time, the ANN model proves to be faster and more suitable for ozone classification in the El Paso, Texas area.展开更多
文摘From the scope and technical system perspective, this paper sums up the history and current situation of logistics tracking and monitoring standards under international standards and national standards system. Taking the first international standard developed by China in the field of logistics and Internet of Things as an example, it analyzes the status quo and trend of monitoring in logistics, presenting valuable experience for standards development in logistics tracking and monitoring in China.
文摘[Objective] The paper is to construct the logistics tracking management system of tropical agricultural products based on supply chain.[Method] With tropical agricultural products in Hainan as study object,based on logistics supply chain files and electronic tag coding of agricultural products,cold chain temperature and humidity monitoring,vehicle transportation positioning,data exchange of XML Web services and role-based permission dynamic allocation,the multi-level multi-permission and multi-role logistics tracking management system of tropical agricultural products has been established.[Result] The system constructs information exchange platform for various links of logistics supply chain of tropical agricultural products,which realizes the entire quality monitoring and information tracing of agricultural products,thus enhancing the competitiveness of supply chain in company.[Conclusion] The system has good application and extension prospect.
文摘Tyre pressure monitoring system(TPMS)is compulsory in most countries like the United States and European Union.The existing systems depend on pressure sensors strapped on the tyre or on wheel speed sensor data.A difference in wheel speed would trigger an alarm based on the algorithm implemented.In this paper,machine learning approach is proposed as a new method to monitor tyre pressure by extracting the vertical vibrations from a wheel hub of a moving vehicle using an accelerometer.The obtained signals will be used to compute through statistical features and histogram features for the feature extraction process.The LMT(Logistic Model Tree)was used as the classifier and attained a classification accuracy of 92.5%with 10-fold cross validation for statistical features and 90.5% with 10-fold cross validation for histogram features.The proposed model can be used for monitoring the automobile tyre pressure successfully.
文摘According to the development trend of intelligent logistics in our country, combining database, communication, GIS （Geography lnfolrnation System） technology, the paper study the key core technology of each module monitoring platform for vehicle monitoring system, and establish logistics transport vehicle monitoring platform that oriented small and medium-sized logistics enterprises, to realize the whole process of real-time monitoring for logistics and transport the vehicle from the warehouse to transportation, promote the informationization of logistics and transport.
文摘The study of the logistics system mode based on the city construction is mainly according to the concrete characteristics of the logistics operation, to sum up the characteristics of the logistics system in the area of the set of the logistics information system, which aims to design a reasonable response model fi＇amework of the logistics system. This research is mainly based on the research on the GPS system, and deepening the logistics information system is to design and construct the function combination of the countermeasures of the logistics information technology, which is to design a complete system framework of the working state, hi addition to the related GIS technology, and the implementation of the monitoring and the control of the logistics information system, and the implementation of the navigation guidance in a reasonable range, provide the reference for the conslraction plan of the whole system, which lays a theoretical foundation for the healthy and effective operation of the countermeasures of the logistics information technology
文摘This paper focuses on ozone prediction in the atmosphere using a machine learning approach. We utilize air pollutant and meteorological variable datasets from the El Paso area to classify ozone levels as high or low. The LR and ANN algorithms are employed to train the datasets. The models demonstrate a remarkably high classification accuracy of 89.3% in predicting ozone levels on a given day. Evaluation metrics reveal that both the ANN and LR models exhibit accuracies of 89.3% and 88.4%, respectively. Additionally, the AUC values for both models are comparable, with the ANN achieving 95.4% and the LR obtaining 95.2%. The lower the cross-entropy loss (log loss), the higher the model’s accuracy or performance. Our ANN model yields a log loss of 3.74, while the LR model shows a log loss of 6.03. The prediction time for the ANN model is approximately 0.00 seconds, whereas the LR model takes 0.02 seconds. Our odds ratio analysis indicates that features such as “Solar radiation”, “Std. Dev. Wind Direction”, “outdoor temperature”, “dew point temperature”, and “PM10” contribute to high ozone levels in El Paso, Texas. Based on metrics such as accuracy, error rate, log loss, and prediction time, the ANN model proves to be faster and more suitable for ozone classification in the El Paso, Texas area.
