Intelligent greenhouse monitoring system based on wireless sensor network

This paper designs an intelligent greenhouse monitoring system to achieve the purpose of intelligent and precise acquisition, storage, and transmission of various data.The main control chip of the system is the STM32F103C8T6 minimum system board, which uses soil moisture sensors, photoresistors, temperature and humidity sensors, raindrop sensors, CO2 sensors, and other sensors to collect data.An OLED display shows the monitored data on site, and an ESP8266 module transmits the data to the ONENET cloud platform via Wi-Fi.Then, an abnormal indoor parameter generates a high-level trigger to activate the buzzer alarm.After physical testing, the intelligent monitoring system can achieve intelligent monitoring of various environmental data such as indoor and outdoor temperature and humidity, light intensity, and air quality.

With the rapid development of automobile technologies and great economic growth, cars have become more and more popular for their convenience. However, the increase in cars has caused serious air pollution and increased the probability of traffic accidents. This paper investigates the design and implementation of intelligent monitoring and early warning system, which can detect the traffic conditions and provide environmental monitoring data. To achieve a comprehensive monitor for both inside and outside the public transport, this system is based on the STC12C5A16S2 micro-controller and loaded with all kinds of sensors, such as alcohol sensors, temperature and humidity sensors, toxic gas sensors, photosensitive sensors and light sensors etc. If the system detects any abnormal situation, it will generate early warning signs in time to inform the driver and the traffic regulatory departments. Consequently, our intelligent monitoring system can protect the safety of passengers and reduce the incidence of traffic accidents.

The thesis deals with the design of intelligent household environment monitoring equipment by the use of ZigBee technology. The system design takes STC12c5a60s2 single-chip microcomputer as the core module of data acquisition terminal. It is a ZigBee-based wireless sensor network acquisition system with low complexity, low power consumption and low cost. The sensor data display capabilities are realized through the single-chip microcomputer. The design mainly consists of the ZigBee wireless sensor network, a single-chip computer and a display device, with the single-chip computer as its core controller. The ZigBee chip CC2530 builds a wireless network for the core, carries temperature/humidity sensors, smoke sensor and infrared sensing devices, which constitute a complete environmental data acquisition system. Introduction With the constant development of wireless telecommunication technology, wireless sensor network has expanded from the earlier military field to industry, science and medicine and is playing an increasingly important role [1]. Wireless sensor network data acquisition technology has evolved from simplification to integration and networking. The ZigBee is a wireless network technology which is a low rate personal area. It’s suitable for such occasions which not amount of data communication, relatively low data transmission speed, a high degree of data security and low power consumption [2]. The thesis deals with the indoor environment monitoring of intelligent households. The sensor network tests the data and the tested data are sent to the acquisition terminal wirelessly. The acquisition terminal analyzes data packet, extracts valid data and displays them on LED 12864. System Design Layout and Device Choice 1. System Framework Layout The system mainly consists of acquisition terminal and sensor network. The whole structure is illustrated in Fig. 1. The acquisition terminal uses a core controller STC12c5a60s2 single-chip computer which is 8-Bit, low-power-consumption and manufactured by domestic corporations. The computer communicates with the coordinator through the serial port. The coordinator ZigBee receives data sent from wireless acquisition node. The core controller analyzes the collected data, extracts valid data and displays them on LCD12864. The sensor network consists of ZigBee node merging sensors.

Multimedia sensor network is regarded as a brand-new information acquisition and processing technology. It pays more attention to acquisition and processing of audio, video, images and other media with large data size and large information content compared with traditional sensor network. The network has broad application prospects. In the paper, intelligent warehouse monitoring system based on multimedia sensor network integrating multi-sensor sets, distributed processing and event-triggered monitoring is designed and developed. The system is based on construction of wireless sensor network and video monitoring network. Wireless sensor network is established by scalar sensor nodes by using IEEE 802.15.4/ZigBee protocol, and it is responsible for collecting and processing scalar data, and transmitting results to sink node. Video monitoring network is composed of multimedia sensor nodes by using Ethernet. Monitoring data, compressed video/audio streaming and other multimedia data of sink node on wireless sensor network are sent to the monitoring center and users. The system can better provide warehouse environment parameter monitoring, event-triggered or continuous remote monitoring functions.

A intelligent monitor and control system on multi-factor of aquaculture environment based on wireless sensor networks is designed adopting BP neural networks. The system uses wireless sensor nodes to detect a variety of water quality parameters transmitted to the on-site monitoring host computer through sink node wirelessly. The control module consists of fuzzy controller and decoupling neural network without the need of environmental model identification. Remote monitoring and control computer using GPRS wireless communication technology allows remote data collection and monitoring of aquaculture to achieve intelligent control and information sharing.

Towards automated greenhouse: A state of the art review on greenhouse monitoring methods and technologies based on internet of things

In order to better ensure the effective operation of substation intelligent auxiliary monitoring system, aiming at the problems of slow data transmission speed and poor data processing security of current monitoring system, a high-speed data transmission method of the substation intelligent auxiliary monitoring system is proposed. By constructing the data processing platform of substation intelligent auxiliary monitoring system, the data transmission algorithm of auxiliary monitoring system is optimized, reasonably select the optimal path of data transmission and conduct security encryption processing, so as to improve the high-speed data transmission efficiency of substation intelligent auxiliary monitoring system. Finally, the experiment shows that the high-speed data transmission method of the substation intelligent auxiliary monitoring system has higher practicability in the process of practical application and fully meets the research requirements.

Intelligent battery management system in a smart farm has a very significant role for energy management. It gives the energy demand status of the entire farm, the available energy produced by the PV system, and the energy stored in the batteries. However, it is important that energy monitoring system to be efficient, most especially in optimizing the distribution of the available harvested energy. Also, since the loads will come from various systems such as aquaponics, vision system, irrigation system and communication systems, efficient system is a necessity. Therefore, it is necessary to have an intelligent monitoring system that will acquire all the possible energy demands of each respective system loads. With the aid of smart farming technology, accurate energy monitoring and distribution is made possible. To properly manage the use of energy harvested for smart farm system loads, this study discusses the design of a fuzzy logic-based intelligent battery management monitoring system (FLi-BMS) to optimize the energy distribution to several loads in the smart farm.

In order to meet the need of water quality in nuclear power plants, an intelligent water quality monitoring system for the water intake of nuclear power plants was designed. The system is a diversified intelligent water quality monitoring system with parameters of main monitoring temperature, ammonia nitrogen content, chlorophyll content and other parameters and underwater camera conditions as well. The paper used STC89C52RC microcontroller and the corresponding sensor underwater to collect water-quality data and sent them to the water surface by wired transmission. It built a wireless Ad hoc network through the nRF24L01 modules to accomplish the data transmission. And the LabViewplatform is adopted as the monitoring center to achieve data monitoring, early warning and analysis. The test results show that the system is suitable for water quality monitoring of nuclear power plant water intake.

To solve the inspection problems in cotton storage, as well as the need for environmental monitoring in the process of modern cotton bale storage, an intelligent inspection and temperature and humidity intelligent monitoring system based on RFID cotton bale was developed by adopting RFID (Radio Frequency Identification) technology, wireless temperature and humidity real-time monitoring technology and handheld terminal intelligent inspection technology. The system was composed of RFID positioning inspection module and temperature and humidity real-time monitoring and transmission module. The artificial neural network (ANN) based on the particle swarm optimization (PSO) algorithm was used to process the monitoring data of the system by Gaussian filtering, and an accurate classification model of RSSI and label position was established. The test results showed that: Through the comparative analysis of the RFID indoor positioning algorithm, the positioning error of the PSO-ANN algorithm was small. In the actual cotton bale warehouse test, the relative error of positioning and monitoring for RFID cotton bale intelligent inspection and monitoring system was less than 6.7%, which effectively improved the working efficiency of inspection personnel and the security of cotton bale storage. The relative error of temperature and humidity was less than 8% and less than 7%, which could display the temperature and humidity information in real time and meet the real-time demand. This study improved the management personnel's effective positioning and inspection of the cotton bale, prevented the loss of cotton bale, reduced the deterioration probability of cotton bale, and effectively improved the storage management level of the cotton bale. It was of great practical significance to realize the networking, automation, and intelligence of cotton bale storage management.

Intelligent field monitoring system for cruciferous vegetable pests using yellow sticky trap images and an improved Cascade R-CNN

In order to solve the problems of complicated wiring, difficult maintenance and easy line corrosion in traditional greenhouse monitoring system, a greenhouse intelligent information monitoring system based on wireless sensor network was developed. In which ZigBee wireless sensors were used to collect field environmental parameters, such as indoor temperature, indoor humidity, light intensity, carbon dioxide concentration, soil humidity and etc. The information center interface was designed by Kingview, which can realize centralized monitoring, data display, data storage and data mining. The system can monitor and control greenhouse environment parameters, with four control modes, i.e. manual control, automatic control, intelligent control and remote control. The system has been applied in demonstration base for three years, and it has been shown that it is accurate, reliable, stable and friendly UI, which could meet the requirements in the modern management of solar greenhouse.

Creating intelligent information processing systems for monitoring complex technical objects and systems is an important task today. This paper presents the principles and models for creating systems of this class. The decision-making process in intelligent information-measuring monitoring systems is described. The article presents a model of intelligent monitoring system and a model of decision-making in intelligent monitoring systems. The presented model of decision-making in intelligent monitoring systems allows estimating the efficiency of their functioning. The article proposes a structural scheme reflecting the sequence of decision-making tasks.

To reduce the losses caused by fire, this paper proposes an intelligent fire monitoring system based on multi-sensor data fusion. Through the design of the temperature, smoke and flame sensors, based on the weighted least squares WLS and improved fuzzy support degree of similar sensors and dissimilar sensors data fusion, respectively, in the ZigBee wireless network based on the design of the fire remote monitoring and control alarm for monitoring, and add the local storage and emergency module. In addition, whether the router nodes work on the ZigBee wireless network during the fire test depends on multi-sensor data fusion. The test shows that the node communication distance is extended and can reach the acceptable requirements in the range of 70m, the highest probability of fire occurrence is 0.92, the lowest probability is 0.14, the overall probability of occurrence is in the range of 0.4 to 0.6, and the error between the predicted value of the probability of occurrence of the fire and the expected value is within ±0.05.

As the biosensor technology rapidly develops, the application of flexible sensors in health monitoring is receiving increasing attention. To achieve high-precision, non-invasive, and continuous blood pressure monitoring, a flexible pulse biosensor based on modified multi-walled carbon nanotubes is studied, designed, and prepared. The sensor adopts a dual conductive layer resistive structure and combines crack structure design to enhance the sensitivity and response speed of the sensor. This design fully considers the biomechanical properties to ensure that the sensor can adapt to the strain changes caused by human movement, thereby improving the accuracy and reliability of monitoring. In addition, the study combines time-frequency analysis methods with fast Fourier transform to extract key feature points of pulse signals and uses a BPNN model to predict current blood pressure values. The results show that within a small strain range, the response time of the sensor is only 56.14 ms, and the strain coefficient is as high as 1572.4, effectively achieving real-time monitoring. This high response speed and sensitivity enable the sensor to accurately capture changes in pulse waveforms related to biomechanics, providing more reliable data support. The error of the average arterial pressure obtained by the prediction model is only −0.070 mmHg, which proves the accuracy of the current blood pressure value prediction. In summary, the intelligent flexible pulse monitoring system based on biosensors studied can achieve high-precision real-time blood pressure measurement and has good stability and anti-interference ability, providing effective technical support for home health management and early monitoring of hypertension. This research not only promotes the development of biosensor technology but also provides a new research direction in the field of biomechanics.