Intelligent Cloud Platform Research Articles

Typical Applications of IoT Cloud Technology in the HVAC Industry

(Objective) Use the Internet of Things and cloud data technology to build intelligent HVAC environment, form the whole ecosystem with cloud technology as the core, running through designers, builders and managers. The application of virtualization based on cloud technology can integrate environmental resources, provide virtual resources such as intelligent management and control and intelligent construction, and provide an intelligent cloud platform for the whole HVAC environment. With the help of big data technology, we can effectively integrate the information of various building structures to reduce the duplication of labor in the design, construction and use process. In this way, we can create an intelligent HVAC environment, and can carry out interactive construction in the new interactive mode, but also can build a cloud platform of HVAC resource sharing, as well as a centralized control of intelligent management center, to achieve multi-dimensional construction and intelligent management. (Conclusion) The intelligent HVAC environment integrated with the Internet of Things cloud technology can realize the effective sharing of resources through the integration of various material resources, thus greatly improving the efficiency of subsequent maintenance.

A NEW METHOD FOR IMPROVING THE ECOLOGICAL ENVIRONMENT INDEX BASED ON DOWNSCALING OF LAND SURFACE TEMPERATURE

Abstract. In the process of urban construction and development, the ecological environment has always been an important consideration factor. How to quickly monitor the long-term ecological environment quality changes in large urban areas is currently one of the main research hotspots. With the continuous development of remote sensing intelligent cloud computing technology, the application of remote sensing methods to monitor urban ecological environment quality changes is becoming more efficient and convenient. Based on the remote sensing ecological index (RSEI) on the remote sensing intelligent cloud platform Google Earth Engine (GEE), this article innovatively proposes an improved remote sensing ecological index (DS-RSEI, Downscale-RSEI). Using the normalized difference vegetation index (NDVI) and land cover data (LULC), terrain data as auxiliary data, the method of moving window and principal component analysis is used to implement spatial downscaling of the heat components in the index, which increases the resolution of the original MODIS land surface temperature (LST) 1000-meter resolution product to 500 meters. When fusing with other images, it can supplement missing image details and improve the ability to evaluate the ecological spatial details of complex urban blocks. Through a comparative analysis of the RSEI index and the DS-RSEI index proposed in this article, it can be seen that DS-RSEI can express the details of ecological environment changes better in complex blocks.

The promotion path of high-quality development of rural tourism based on intelligent cloud platform system

Abstract With the continuous development of the economy and the level of science and technology, people are no longer satisfied with the old rural tourism model, and information technology is developing rapidly, which brings an opportunity for developing rural tourism innovation. As a product of the comprehensive development of the information age in recent years, “Internet+Rural Tourism” builds an intelligent cloud platform for rural information services relying on big data and other advantages and establishes a rural intelligent tourism service system to provide convenient, intelligent, and diversified services for tourists. This paper elaborates on the practical significance of “Internet + rural tourism” development opportunities”. It proposes to scientifically calculate the environmental capacity of rural eco-tourism areas, control the scale of visitors and reasonably invest in costs because of the problems of lagging infrastructure facilities and limited distribution of inputs and outputs in the process of its development. The results of this paper show that the satisfaction level of rural tourism tourists is the lowest, with the degree of “dissatisfaction” as high as 38.40%; in the rating of rural tourism indicators, the rating of rural ecological environment is only 52.41, the average rating of rural economic indicators is 60.12, and the average rating of comprehensive management indicators is 58.2. The results of this paper also illustrate that the current rural tourism development has three major problems: environment, economy, and management and that rural tourism should not blindly invest high costs if it wants to seek high-quality development but should seek long-term development of rural tourism based on its characteristics and rural ecological environment indicators.

미세전자기계시스템(MEMS) 센서를 활용한 사물인터넷용 다용도 측정기 설계 및 구현

In this study, based on recent technologies such as the Internet of Things, cloud computing, wearables, and artificial intelligence, a multi-purpose measuring device, which is a practice equipment for AI application education based on MEMS, was developed. It was linked with an intelligent cloud platform to check the measurement results on the web. Therefore, circuits using BME280 temperature and humidity measurement sensors and CCS811 gas(pressure) sensors were designed. The artwork and PCB for the integration of the two sensors were manufactured to develop a multi-purpose measuring device for the Internet of Things based on the ESP32 main board. In addition, for user convenience and visualization of observation results, it was linked with an intelligent cloud platform to clearly observe the results on the web.

Rapid construction of modular buildings for emergencies: a case study from Hong Kong, China

A new wave of the Covid-19 pandemic struck Hong Kong in February 2022. It led to construction of a temporary 1000-bed hospital and 10 000-bed isolation and treatment facility on an island site in just 51 days using factory-made modules. To achieve such rapid construction, module assembly was carried out at a separate site between the factories and site. Several new modular construction technologies were also developed, including adjustable base supports, large-span roof modules, universal safety barriers and an intelligent cloud platform for construction management. But to enable sustainable construction of such emergency buildings in future, further studies on demolition, recycling and relocation of modular buildings need to be carried out in the post-pandemic era.

Information Technology Enabling College English Teaching: Bottleneck and Breakthrough

The deep integration of information technology and college English teaching is a new way to realize the informatization and intelligence of college English education. The author proposes that in order to deeply integrate information technology and enable college English teaching, immersion teaching mode can be adopted to establish a framework for cultivating diversified students' autonomous learning ability, and an information-based teaching mode of college English can be built based on the intelligent cloud platform, so as to realize the information and intelligence of foreign language education and promote the further development of college English teaching in China in the new era.

English Multimedia Online Teaching Resource Processing System Based on Intelligent Cloud Platform

In order to improve the quality of online English teaching, starting from English online teaching resources, this paper applies cloud computing technology to the teaching resource integration process to design a comprehensive cloud storage control method based on user habits. Moreover, this paper uses the user habit extraction algorithm to extract the user’s habit information and then realizes the control of cloud storage with the help of these habit information. After that, the system can realize intelligent management of cloud storage in space by analyzing the information and converting it into corresponding cloud storage control instructions. In addition, this paper constructs an integrated system of English multimedia network teaching resources under the support of cloud storage technology. Finally, this paper uses simulation experiments to verify that the integrated system of English multimedia network teaching resources based on cloud storage has a good effect.

Research on Application of Edge Computing in Real-time Environmental Monitoring System

In order to solve the problem of insufficient data processing ability and high delay of cloud computing in environmental monitoring system, combined with edge computing technology, this paper designs an environmental monitoring system which can process data in real time. The system uses the Baetyl edge computing frame to build an edge node on Raspberry Pi, the monitoring node collects environmental data such as temperature and humidity and sends the data to the edge node. The edge node will upload the monitoring data to Baidu Intelligent Cloud Platform after processing. The test results show that edge computing has obvious advantages in the application of environmental monitoring.

A Multidimensional Information Fusion-Based Matching Decision Method for Manufacturing Service Resource

With the development of specialization, coordination and intelligence in the manufacturing service process, the issue of how to quickly extract potential resources or capabilities for distributed manufacturing service requirements, and how to carry out resource matching for manufacturing service requirements with correlated mapping characteristics, have become the critical issues to be addressed in the cloud manufacturing environment. Through the combination of the characteristics of relevance, synergy and diversity of manufacturing service tasks on the intelligent cloud platform, a matching decision method for manufacturing service resources is proposed in this paper based on multidimensional information fusion. On the basis of integrating multidimensional information data in cloud manufacturing resource, the information entropy and rough set theory are applied to classify the importance of manufacturing service tasks, while the matching capability are analyzed by using a hybrid collaborative filtering (HCF) algorithm. Then, the information of function attribute, reliability and preference is employed to match and push manufacturing service resources or capabilities actively, so as to realize the matching decision of manufacturing service resources with precise quality, stable service and maximum efficiency. At last, a case study of resources matching decision for body & chassis manufacturing service in a new energy automobile enterprise is presented, in which the experimental results show that the proposed approach is more accuracy and effective compared with other different recommendation algorithms.

A prospective cohort study of home blood pressure monitoring based on an intelligent cloud platform (the HBPM-iCloud study): rationale and design.

Background:Hypertension, as a predominant risk factor for cardiovascular disease, is a severe public health burden in China. Home blood pressure monitoring (HBPM) is an important tool in the detection and management of hypertension. However, there is a lack of HBPM data from prospective cohorts in China. Hence, we designed this study to investigate the impact of HBPM on major health outcomes in Chinese population participating in regular health check-ups.Methods:Leveraging telemedicine technology, the open prospective, multicenter, HBPM-iCloud (Home Blood Pressure Monitoring Based on an Intelligent Cloud Platform) cohort study will recruit participants from three participating health check-up centers in southern China to participate in cloud-based HBPM for 1 week. The prevalence of sustained hypertension, white coat hypertension (WCH), masked hypertension (MH), white coat uncontrolled hypertension (WUCH), and masked uncontrolled hypertension (MUCH) will be defined by a combination of average readings of home-based and office-based blood pressure (BP). Cardiovascular risk factors and subclinical target organ damage will be recorded. Participants will be followed-up for 5 years to examine the incidence and associated risk factors of composite major adverse cardiovascular and cerebrovascular event.Conclusion:The study will help to determine the best way to implement telemedicine technology in BP control for better prevention and treatment of hypertension. Results will provide data for a Chinese population to aid in the construction of screening, risk stratification, and intervention strategies for abnormal BP phenotypes, including WCH, MH, WUCH, and MUCH.

Application of face image detection based on deep learning in privacy security of intelligent cloud platform

The application of deep learning-based face detection in the privacy and security of intelligent cloud platforms is studied, in order to resolve the risk of private photo leakage on such platforms. Five key feature points of human faces (two eyes, two noses and two corners of mouth) are sought using the multitask cascaded convolution network (MTCNN). The algorithm utilizes the intrinsic links among Proposal Network (P-Net), Refine Network (R-Net) and Output Network (O-Net) to improve their face detection performances substantially. Since many existing data encryption methods, such as DES, RSA and AES, are applicable only to test data instead of digital images, the encryption of eigenvalues is achieved with a combination of chaotic logic diagrams and RC4 stream ciphers. Meanwhile, the MTCNN-generated face coordinates and user passwords are hash-converted and double-encrypted using hash table. The results show that the face detection accuracy of MTCNN reaches 95.04%, and that the image encryption method is suitable for network transmission. The chaotic logic diagrams increase the security of S-box initialization in the RC4 algorithm. The hash structure accelerates the file reading, whereas the hash conversion improves the security of critical data. In conclusion, the proposed encryption scheme is computationally fast and highly secure.

Electric Vehicle Intelligent Service Cloud Platform

In recent years, electric vehicles have developed rapidly around the world. A series of research and services for electric vehicles are also rapidly developing. Faced with the broad market demand, Yichang Ju Calling Company launched the intelligent charging and switching service cloud platform “Gathering”. Based on technologies such as Internet of Things, Internet, and big data analysis, the solution builds an intelligent vehicle cloud platform for electric vehicles. The intelligent cloud platform has an electric vehicle charging and reloading reservation, a next destination navigation charging and switching plan, and a private charging pile sharing. Charging pile inquiry and reservation, fee settlement, user community communication and other functions make the electric vehicle charging service platform more intelligent and convenient. At the same time, as a bridge between electric vehicles and charging stations, “Gathering” can combine the real-time electricity price, the degree of traffic congestion, the use of charging piles and the load of the power grid to plan more efficient and convenient charging suggestions for users. Make full use of power resources to reduce the load and cost of the grid.

A Novel Cloud Platform for Service Robots

With the development of computer technology and artificial intelligence (AI), service robots are widely used in our daily life. While the manufacturing cost of the robots is too expensive for most small technology companies. The biggest technical limitations are the design of the robot service and the resources sharing of the robot groups. As far as we know, there is no complete and open-source service robot cloud service platform. To solve the above problems, in this paper, a novel robot cloud platform called cloud robotics intelligent cloud platform (CRICP) is designed, which consists of gateway layer, an interface layer, service pool, and algorithm layer. Gateway layer mainly solves the problem of robot access control and service invocation requests scheduling. In addition, a standardized access method is proposed to overcome the problem that heterogeneous service robots cannot access the cloud platform. Interface layer is responsible for protocol injection, including motoring protocol, a management protocol, and other algorithms invocation protocol or service invocation interfaces protocol. Service Pool consists of different kinds of robot services which could scale based on the historical data analysis. In Algorithm layer, we can implement machine learning (ML) algorithm, deep learning (DL) algorithm, distributed algorithm, and so on. Finally, voice recognition service invocation experiment and cloud service dynamic scaling test are taken as an example to verify the availability and accuracy of our platform. Moreover, the compared results with a local framework and SOA also verifies the superiority of our platform.