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Web technologies for sensor and energy data models
Published in Pieter Pauwels, Kris McGlinn, Buildings and Semantics, 2023
With the need to connect devices such as sensors through the IoT infrastructure, there is also the need for database services adapted to this new interconnectivity context, provided from the cloud environment itself so that greater scalability can be achieved. This way, in recent years, the concept of cloud database has appeared to refer to database services that run on cloud computing platforms (e.g., Amazon Web Services, Microsoft Azure) [9]. Among the advantages of opting for a cloud database service, there is the ease of combining it with other services provided from the same platform in the cloud (e.g., IoT and analytics components). Likewise, in recent years, some time series databases have appeared provided through web platforms. An example is InfluxDB11, an open source TSDB database with built-in time-centric functions for querying measurement, series and point data. Another example is TimescaleDB12, a time-series SQL database designed to provide fast analytics and scalability with automated data management.
Research on the detection of toxic gases in the environment using APP and the IoTs
Published in Artde Donald Kin-Tak Lam, Stephen D. Prior, Siu-Tsen Shen, Sheng-Joue Young, Liang-Wen Ji, Innovation in Design, Communication and Engineering, 2020
The APP software is connected to the cloud network layer, the sensor component of the sensing layer, and the application layer after the data is collected. Based on the IoT architecture, it is designed for automatic CO, GAS concentration detection and remote truncated gas systems. The system is divided into three parts, as explained below: Perceptual layer: Embedded chip built-in Bluetooth wireless communication technology will instantly detect the CO content and gas flow. The detector will return the CO content and gas flow to the host server. And when the CO and GAS concentrations are too high, the app will notify the monitoring unit of the message.Data back-transmission technology adopts Bluetooth wireless communication protocol, which fully complies with the design of IoT architecture, has low power consumption, low power, and meets the rapid growth trend of the wireless connection market in the world in the future.Embedded wafers, in addition to installed CO, GAS content sensors and gas flow sensing, at least 10 sensor components can be expanded. If the system needs to increase the sensing components at any time in the future, it can be customized according to the needs.Network layer: The embedded chip collects the CO and GAS concentration data and returns it to the host server. The host server schedules the application to periodically upload data to the cloud server database.The cloud database collects concentration data at various time points, mainly for establishing a database of big data. It can be used to integrate and analyze intelligent systems in the future.Consider the importance of the cloud database, the cloud server automatically schedules backup of all data.Cloud data transmission is based on https transmission security agreementApplication layer Smart Cloud Interface Design; (B) User Management System: (C) Limited Management System; (D) CO、GAS Content Detection. The system software and hardware operation architecture is shown in Figure 3, the APP and Equipment architecture diagram is shown in Figure 4.
A BIM-based framework for road construction quality control and quality assurance
Published in International Journal of Pavement Engineering, 2023
Chengjia Han, Tao Han, Tao Ma, Zheng Tong, Siqi Wang
The BIM-based framework proposed in this paper for road construction QC&QA is shown in Figure 1. Five stages are included in this framework according to the five subsections in Section 2. Firstly, the on-site construction data is generated from different construction sections and recorded by technicians using data terminal equipment such as smart phones. Secondly, the collected data is automatically uploaded to the data interaction and processing centre, which is deployed in a cloud database. After that, a road BIM model is built based on the design and construction transmission data. Then, a BIM-based platform is established based on BIM model, which is a carrier of construction data to realise the data integration and visualisation. Finally, the BIM model is used for real-time construction quality control and assurance, which realises the guidance to the road construction sites. The whole framework enables the data interaction and closing the loop between the BIM model and the construction site.
Cloud-based manufacturing process monitoring for smart diagnosis services
Published in International Journal of Computer Integrated Manufacturing, 2018
The cloud computing capability is employed to rapidly perform online diagnostic tasks, and the potentially huge cloud database is used to maintain and share relevant information and knowledge that can support further cloud services.