scholarly journals Internet of Things (IoT) Technology for the Development of Intelligent Decision Support Education Platform

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Jinhua Liu ◽  
Caiping Wang ◽  
Xianchun Xiao
Keyword(s):  
Internet Of Things ◽  
Online Teaching ◽  
College Education ◽  
Management Platform ◽  
Multimedia Teaching ◽  
Intelligent Decision ◽  
Examination Result ◽  
Online Management ◽  
Education Platform ◽  
Intelligent Decision Support

Improving the intelligence of teaching environment and making the multimedia teaching equipment has become a major concern of the colleges and universities. To this end, the design of Internet of Things (IoT) technology based wisdom of higher education platform is of great interest. Designing the structure of online management platform for college education and realizing the functions of examination result inquiry, online teaching, and attendance management have gained more importance in the educational research. The wisdom classroom is the key structure of the wisdom education platform. A smart classroom architecture based on IoT technology is designed, which connects with traditional network facilities through the IoT gateway. Different layers of the architectures have been designed and implemented. The proposed platform tests results and shows that the intelligent education platform can effectively control classroom utilization and has high throughput, low application latency, and good practicability.

scholarly journals PIDS: An Intelligent Electric Power Management Platform

2020 ◽  
Vol 34 (08) ◽  
pp. 13220-13227
Author(s):  
Yongqing Zheng ◽  
Han Yu ◽  
Yuliang Shi ◽  
Kun Zhang ◽  
Shuai Zhen ◽  
...  
Keyword(s):  
Power Consumption ◽  
Stable Operation ◽  
Economic Activities ◽  
Power Outage ◽  
Fine Grained ◽  
Management Platform ◽  
Power Adjustment ◽  
Intelligent Decision ◽  
Information Tracking ◽  
Intelligent Decision Support

Electricity information tracking systems are increasingly being adopted across China. Such systems can collect real-time power consumption data from users, and provide opportunities for artificial intelligence (AI) to help power companies and authorities make optimal demand-side management decisions. In this paper, we discuss power utilization improvement in Shandong Province, China with a deployed AI application - the Power Intelligent Decision Support (PIDS) platform. Based on improved short-term power consumption gap prediction, PIDS uses an optimal power adjustment plan which enables fine-grained Demand Response (DR) and Orderly Power Utilization (OPU) recommendations to ensure stable operation while minimizing power disruptions and improving fair treatment of participating companies. Deployed in August 2018, the platform is helping over 400 companies optimize their power consumption through DR while dynamically managing the OPU process for around 10,000 companies. Compared to the previous system, power outage under PIDS through planned shutdown has been reduced from 16% to 0.56%, resulting in significant gains in economic activities.

scholarly journals Optimizing Smart Grid Operations from the Demand Side

AI Magazine ◽  
2021 ◽  
Vol 42 (2) ◽  
pp. 28-37
Author(s):  
Yongqing Zheng ◽  
Han Yu ◽  
Yuliang Shi ◽  
Kun Zhang ◽  
Shuai Zhen ◽  
...  
Keyword(s):  
Power Grid ◽  
Stable Operation ◽  
Demand Side ◽  
Power Outage ◽  
Fine Grained ◽  
Management Platform ◽  
Intelligent Decision ◽  
Main Components ◽  
Planning And Construction ◽  
Intelligent Decision Support

As demand for electricity grows in China, the existing power grid is coming under increasing pressure. Expansion of power generation and delivery capacities across the country requires years of planning and construction. In the meantime, to ensure safe operation of the power grid, it is important to coordinate and optimize the demand side usage. In this paper, we report on our experience deploying an artificial intelligence (AI)–empowered demand-side management platform – the Power Intelligent Decision Support (PIDS) platform – in Shandong Province, China. It consists of three main components: 1) short-term power consumption gap prediction, 2) fine-grained Demand Response (DR) with optimal power adjustment planning, and 3) Orderly Power Utilization (OPU) recommendations to ensure stable operation while minimizing power disruptions and improving fair treatment of participating companies. PIDS has been deployed since August 2018. It is helping over 400 companies optimize their power usage through DR, while dynamically managing the OPU process for around 10,000 companies. Compared to the previous system, power outage under PIDS due to forced shutdown has been reduced from 16% to 0.56%.

An Integrated Legacy of Modbus Devices to Industrial Internet of Things: Approach for Smart Industries

2020 ◽  
Author(s):  
Karthik Muthineni
Keyword(s):  
Internet Of Things ◽  
Industrial Revolution ◽  
Digital Technologies ◽  
Industrial Internet Of Things ◽  
Intelligent Decision Making ◽  
Internet Of Everything ◽  
Industrial Internet ◽  
Intelligent Decision ◽  
Network Platform ◽  
Smart Factories

The new industrial revolution Industry 4.0, connecting manufacturing process with digital technologies that can communicate, analyze, and use information for intelligent decision making includes Industrial Internet of Things (IIoT) to help manufactures and consumers for efficient controlling and monitoring. This work presents the design and implementation of an IIoT ecosystem for smart factories. The design is based on Siemens Simatic IoT2040, an intelligent industrial gateway that is connected to modbus sensors publishing data onto Network Platform for Internet of Everything (NETPIE). The design demonstrates the capabilities of Simatic IoT2040 by taking Python, Node-Red, and Mosca into account that works simultaneously on the device.

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