In view of the complexity combustion process of three-waste boiler, designed the distributedcontrol System based on Windows control Center configuration software and Programmable Logic controller. The system controls...
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With the development of the energy Internet, the terminals of the power Internet of Things are open and interactive, the grid protection boundary is ambiguous, and the traditional boundary based security system is dif...
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ISBN:
(纸本)9783031366246;9783031366253
With the development of the energy Internet, the terminals of the power Internet of Things are open and interactive, the grid protection boundary is ambiguous, and the traditional boundary based security system is difficult to ensure the secure access of the power Internet of things terminals. The program proposed a secure access method for the power system based on the zero-trust architecture. It takes the identity of the terminal as the center to carry out security authentication and dynamic access control. Based on the device fingerprint extraction and the Identification Public Key algorithm, the lightweight security authentication of the power terminal is realized. Through the trust calculation method based on terminal operating characteristics, continuous trust assessment and dynamic access control are carried out. The method is verified in the distributed power security access scenario. For common flood attacks, packet attacks and malicious code attacks, the security access method of the power Internet of Things based on the zero-trust architecture can effectively detect and block them in time, which can avoid attackers from conducting cyber attacks on the grid by controlling power IoT terminals (This work was supported by the State Grid Shanghai Technology Project, Research on Key Technologies for Network Security Access of Power monitoring System Based on Zero Trust.).
In this paper, the expert system of artificial intelligence automatic control system is designed to identify each stage of the internal fermentation reaction process of food waste anaerobic fermentation tank, and comp...
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In this paper, we propose a real-time IoT (Internet of Things) system with a built-in hardware security function, allows the ambient environment monitoring and control actuators via a wireless network at the frequency...
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ISBN:
(纸本)9783030684525;9783030684518
In this paper, we propose a real-time IoT (Internet of Things) system with a built-in hardware security function, allows the ambient environment monitoring and control actuators via a wireless network at the frequency of 433 MHz, a real-time database is used to store and share environmental sensors data and users with a proposed Mobile App can send commands to turn on/off actuators through the Internet. The proposed system was developed and tested using an actuator device (AD) and two type of sensors, CO2 sensor and air-temperature and -humidity sensor. The main components of the proposed IoT system consist of: a proposed IoT gateway, three of sensor nodes and a real-time Firebase database. Detailed components of the proposed sensor node included: a low-power system on chip unit (SoC) with an built-in Wi-Fi module and a RF antenna, a MQ135 sensor and a SHT10 sensor. Based on Firebase database, aMobile App have been designed and used to monitor measured recordings of sensors and as control the AD. A wireless module operates at frequency of 433 MHz with top secret built-in security algorithm (AES128) is selected to encrypt the result of ambient environmental sensor data and as transfer commands to the AD mentioned. In addition, some advantages compared with wired connection networks, and in which the structure of the online database of the proposed IoT system has some additional features and more flexibility. The experiment results with the proposed Mobile App are implemented that the proposed IoT system can be used to monitor ambient environments that live to report of measured sensors and make the information visible anywhere as well as control the AD. Our IoT system can be able use to monitor the ambient environment in wirelessly solutions in large-areas with high-level secure algorithm and control electrical machines in many sectors such smart buildings, smart homes, smart agriculture.
China's agriculture is gradually moving from traditional agriculture to digital agriculture and smart agriculture. Accelerating the breakthrough of key agricultural core technologies and solidly promoting agricult...
China's agriculture is gradually moving from traditional agriculture to digital agriculture and smart agriculture. Accelerating the breakthrough of key agricultural core technologies and solidly promoting agricultural modernization are the key to the development of smart agriculture. intelligentmonitoring of agricultural greenhouses is an important way to realize agricultural modernization. However, most of the existing greenhouses have backward management concepts, low industry development level, lack of a complete and standardized production management system, and low level of agricultural facilities leads to low resource utilization. In the process of agricultural production, it is difficult to scientifically monitor and analyze the indicators such as temperature, light and soil water content, and the application amount of various nutrients in the process of crop growth can not be accurately controlled, which affects the agricultural planting benefits. Based on this, the author designed an agricultural greenhouse monitoring system based on the Internet of things. The system uses STM32 as the main control chip and is connected with a series of sensors to monitor the environmental parameters in the greenhouse in real time and adjust the environmental parameters in the greenhouse in time, so as to achieve the set standards, adjust the growth cycle, improve quality and increase production.
The items are a software solution, it is designed for micro grids with energy storage integration to monitor, control, and best utilize available grid resources. Also called a mini-grid, the micro grid is a distribute...
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ISBN:
(数字)9798331542375
ISBN:
(纸本)9798331542382
The items are a software solution, it is designed for micro grids with energy storage integration to monitor, control, and best utilize available grid resources. Also called a mini-grid, the micro grid is a distributed energy system consisting of local small-scale generation and storage facilities that could operate independently from the main grid in an emergency. Micro grids are frequently paired with solar panels and wind turbines, making them more sustainable. The capacity of energy storage systems in micro grids has been playing an important role, as renewable energy in devices with temporal availability generates the need for their more efficient use. Based on real-time data, the items apply energy transmission and distribution management algorithms to control where the power is used in a micro grid. The items continuously monitor the demand and supply of energy to investigate the ideal combination of renewable generation and stored energy for peak shaving. In doing so, the micro grid can run optimally and minimize energy waste without running up bills. The items can also predict how and when individuals use energy, thus allowing better scheduling of the available resources. This enables the items to conduct predictive maintenance on those micro grid components to long and function as efficiently as possible.
Aiming at the security requirements of smart community, an intelligent inspection robot was present in this paper. The environmental characteristics of the smart community were described in detail, and the characteris...
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LoRa is a long-range, low-power, low-bitrate communication technology that is a major component of the Internet of Things (IoT). In realizing smart cities, many environmental parameters are observed in decision making...
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This work presents and implements a low-cost irrigation system for smart agriculture that is based on the Internet of Things (IoT). In order to continuously monitor environmental data in real time, the system is equip...
This work presents and implements a low-cost irrigation system for smart agriculture that is based on the Internet of Things (IoT). In order to continuously monitor environmental data in real time, the system is equipped with a network of sensors, including pressure, temperature, moisture, and water level sensors. In order to anticipate when irrigation pumps will switch on, machine learning techniques including Artificial Neural Networks (ANN), Decision Trees (DT), Naive Bayes (NB), and Support Vector Machines (SVM) are linked depending on established parameters. The study shows that the ANN model can identify complicated patterns in the agricultural environment with an accuracy of up to 98.33%. Farmers are able to make well-informed decisions quickly thanks to the cloud connectivity and intuitive interface of remote monitoring and control. Because predictive modeling minimizes pump activation delays, it lessens the chance of both over- and under-irrigation. The suggested strategy makes the most use of available water and provides opportunities for precision farming, which is a major step forward for sustainable agriculture. The study's findings demonstrate how well the system uses resources and open the door for the future creation of innovative, scalable agricultural technology.
Smart pollution monitoring approaches based on wireless sensor networks (WSNs) have progressed significantly over the past decade. More recently, intelligent computational strategies based on internet-of-things (IoT) ...
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ISBN:
(纸本)9781665477109
Smart pollution monitoring approaches based on wireless sensor networks (WSNs) have progressed significantly over the past decade. More recently, intelligent computational strategies based on internet-of-things (IoT) and cloud computing (CC) have gained much momentum in the related studies. In this study, a smart context-aware environmental pollution monitoring and control scheme is presented for an urban setting to demonstrate how effective pollution mitigation and control can be achieved by the integration of known hardware and software approaches in a feedback control system. As a main contribution, this work shall describe in detail how the hardware infrastructure that consists of internet-of-things (IoT) and either cellular or non-cellular communications, is combined with machine learning (ML) software algorithms to provide informed environment control decisions/signals for dynamically and optimally updating the status of our environmentally controlled mitigation strategies. Finally, the importance of this work is clear as the framework and architecture can also be applied to other urban settings and mitigation strategies that can be optimized using intelligent and context-aware control signals.
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