IoT-Enabled Plant Monitoring System with Power Optimization and Secure Authentication

Global food security is a pressing issue that affects the stability and well-being of communities worldwide.While existing Internet of Things(IoT)enabled plant monitoring systems have made significant strides in agricultural monitoring,they often face limitations such as high power consumption,restricted mobility,complex deployment requirements,and inadequate security measures for data access.This paper introduces an enhanced IoT application for agricultural monitoring systems that address these critical shortcomings.Our system strategically combines power efficiency,portability,and secure access capabilities,assisting farmers in monitoring and tracking crop environmental conditions.The proposed system includes a remote camera that captures images of surrounding plants and a sensor module that regularly monitors various environmental factors,including temperature,humidity,and soil moisture.We implement power management strategies to minimize energy consumption compared to existing solutions.Unlike conventional systems,our implementation utilizes the Amazon Web Services(AWS)cloud platform for reliable data storage and processing while incorporating comprehensive security measures,including Two-Factor Authentication(2FA)and JSON Web Tokens(JWT),features often overlooked in current agricultural IoT solutions.Users can access this secure monitoring system via a developed Android application,providing convenient mobile access to the gathered plant data.We validate our system’s advantages by implementing it with two potted garlic plants on Okayama University’s rooftop.Our evaluation demonstrates high sensor reliabil-ity,with strong correlations between sensor readings and reference data,achieving determination coefficients(R2)of 0.979 for temperature and 0.750 for humidity measurements.The implemented power management strategies extend battery life to 10 days on a single charge,significantly outperforming existing systems that typically require daily recharging.Furthermore,our dual-layer security implementation utilizing 2FA and JWT successfully protects sensitive agricultural data from unauthorized access.

Value Function Mechanism in WSNs-Based Mango Plantation Monitoring System

Mango fruit is one of the main fruit commodities that contributes to Taiwan’s income.The implementation of technology is an alternative to increasing the quality and quantity of mango plantation product productivity.In this study,a Wireless Sensor Networks(“WSNs”)-based intelligent mango plantation monitoring system will be developed that implements deep reinforcement learning(DRL)technology in carrying out prediction tasks based on three classifications:“optimal,”“sub-optimal,”or“not-optimal”conditions based on three parameters including humidity,temperature,and soil moisture.The key idea is how to provide a precise decision-making mechanism in the real-time monitoring system.A value function-based will be employed to perform DRL model called deep Q-network(DQN)which contributes in optimizing the future reward and performing the precise decision recommendation to the agent and system behavior.The WSNs experiment result indicates the system’s accuracy by capturing the real-time environment parameters is 98.39%.Meanwhile,the results of comparative accuracy model experiments of the proposed DQN,individual Q-learning,uniform coverage(UC),and NaÏe Bayes classifier(NBC)are 97.60%,95.30%,96.50%,and 92.30%,respectively.From the results of the comparative experiment,it can be seen that the proposed DQN used in the study has themost optimal accuracy.Testing with 22 test scenarios for“optimal,”“sub-optimal,”and“not-optimal”conditions was carried out to ensure the system runs well in the real-world data.The accuracy percentage which is generated from the real-world data reaches 95.45%.Fromthe resultsof the cost analysis,the systemcanprovide a low-cost systemcomparedtothe conventional system.

Development of Spectral Features for Monitoring Rice Bacterial Leaf Blight Disease Using Broad-Band Remote Sensing Systems

As an important rice disease, rice bacterial leaf blight (RBLB, caused by the bacterium Xanthomonas oryzae pv.oryzae), has become widespread in east China in recent years. Significant losses in rice yield occurred as a result ofthe disease’s epidemic, making it imperative to monitor RBLB at a large scale. With the development of remotesensing technology, the broad-band sensors equipped with red-edge channels over multiple spatial resolutionsoffer numerous available data for large-scale monitoring of rice diseases. However, RBLB is characterized by rapiddispersal under suitable conditions, making it difficult to track the disease at a regional scale with a single sensorin practice. Therefore, it is necessary to identify or construct features that are effective across different sensors formonitoring RBLB. To achieve this goal, the spectral response of RBLB was first analyzed based on the canopyhyperspectral data. Using the relative spectral response (RSR) functions of four representative satellite or UAVsensors (i.e., Sentinel-2, GF-6, Planet, and Rededge-M) and the hyperspectral data, the corresponding broad-bandspectral data was simulated. According to a thorough band combination and sensitivity analysis, two novel spectralindices for monitoring RBLB that can be effective across multiple sensors (i.e., RBBRI and RBBDI) weredeveloped. An optimal feature set that includes the two novel indices and a classical vegetation index was formed.The capability of such a feature set in monitoring RBLB was assessed via FLDA and SVM algorithms. The resultdemonstrated that both constructed novel indices exhibited high sensitivity to the disease across multiple sensors.Meanwhile, the feature set yielded an overall accuracy above 90% for all sensors, which indicates its cross-sensorgenerality in monitoring RBLB. The outcome of this research permits disease monitoring with different remotesensing data over a large scale.

Design and Construction of Automatic Monitoring System for Open-pit Coal Mine Slopes

[Objectives]To monitor the stability of open-pit coal mine slopes in real time and ensure the safety of coal mine production.[Methods]The automatic monitoring system of coal mine slope was explored in depth,and the core functions of the system were designed comprehensively.According to the design function of the automatic monitoring system,the slope automatic monitoring system was constructed.Besides,in accordance with the actual situation of the slope,the monitoring frequency of slopes was set scientifically,and the key indicators such as rainfall,deep displacement and surface displacement of the slopes were monitored in an all-round and multi-angle way.[Results]During the monitoring period,the overall condition of the slope remained good,and no landslides or other geological disasters occurred.At the same time,the overall rainfall in the slope area remained low.In terms of monitoring data,the horizontal displacement and settlement of the slopes increased first and then tended to be stable.Specifically,the maximum horizontal displacement during the monitoring period was 22.74 mm,while the maximum settlement was 18.65 mm.[Conclusions]The automatic slope monitoring system has obtained remarkable achievements in practical application.It not only improves the accuracy and efficiency of slope stability monitoring,but also provides valuable reference experience for similar projects.

Long-term trends in the abundance and breeding performance in Adélie penguins:the Argentine Ecosystem Monitoring Program

In this work,we report long-term trends in the abundance and breeding performance of Adélie penguins(Pygoscelis adeliae)nesting in three Antarctic colonies(i.e.,at Martin Point,South Orkneys Islands;Stranger Point/Cabo Funes,South Shetland Islands;and Esperanza/Hope Bay in the Antarctic Peninsula)from 1995/96 to 2022/23.Using yearly count data of breeding groups selected,we observed a decline in the number of breeding pairs and chicks in crèche at all colonies studied.However,the magnitude of change was higher at Stranger Point than that in the remaining colonies.Moreover,the index of breeding success,which was calculated as the ratio of chicks in crèche to breeding pairs,exhibited no apparent trend throughout the study period.However,it displayed greater variability at Martin Point compared to the other two colonies under investigation.Although the number of chicks in crèche of Adélie penguins showed a declining pattern,the average breeding performance was similar to that reported in gentoo penguin colonies,specifically,those undergoing a population increase(even in sympatric colonies facing similar local conditions).Consequently,it is plausible to assume a reduction of the over-winter survival as a likely cause of the declining trend observed,at least in the Stranger Point and Esperanza colonies.However,we cannot rule out local effects during the breeding season affecting the Adélie population of Martin Point.

Research on the monitoring system for induced voltage and ground current of 27.5 kV cable sheath in railways

Purpose–The purpose of this study is to address the deficiency in safety monitoring technology for 27.5 kV high-voltage cables within the railway traction power supply by analyzing the grounding methods employed in high-speed railways and developing an effective monitoring solution.Design/methodology/approach–Through establishing a mathematical model of induced potential in the cable sheath and analyzing its influencing factors,the principle of grounding current monitoring is proposed.Furthermore,the accuracy of data collection and alarm function of the monitoring equipment were verified through laboratory simulation experiments.Finally,through practical application in the traction substation of the railway bureau on site,a large amount of data were collected to verify the stability and reliability of the monitoring system in actual environments.Findings–The experimental results show that the designed monitoring system can effectively monitor the grounding current of high-voltage cables and respond promptly to changes in cable insulation status.The system performs excellently in terms of data collection accuracy,real-time performance and reliability of alarm functions.In addition,the on-site trial results further confirm the accuracy and reliability of the monitoring system in practical applications,providing strong technical support for the safe operation of highspeed railway traction power supply systems.Originality/value–This study innovatively develops a 27.5kV high-voltage cable grounding current monitoring system,which provides a new technical means for evaluating the insulation status of cables by accurately measuring the grounding current.The design,experimental verification and application of this system in high-speed railway traction power supply systems have demonstrated significant academic value and practical significance,contributing innovative solutions to the field of railway power supply safety monitoring.

Assessing the corrosion protection property of coatings loaded with corrosion inhibitors using the real-time atmospheric corrosion monitoring technique

The atmospheric corrosion monitoring(ACM)technique has been widely employed to track the real-time corrosion behavior of metal materials.However,limited studies have applied ACM to the corrosion protection properties of organic coatings.This study compared a bare epoxy coating with one containing zinc phosphate corrosion inhibitors,both applied on ACM sensors,to observe their corrosion protection properties over time.Coatings with artificial damage via scratches were exposed to immersion and alternating dry and wet environments,which allowed for monitoring galvanic corrosion currents in real-time.Throughout the corrosion tests,the ACM currents of the zinc phosphate/epoxy coating were considerably lower than those of the blank epoxy coating.The trend in ACM current variations closely matched the results obtained from regular electrochemical tests and surface analysis.This alignment highlights the potential of the ACM technique in evaluating the corrosion protection capabilities of organic coatings.Compared with the blank epoxy coating,the zinc phosphate/epoxy coating showed much-decreased ACM current values that confirmed the effective inhibition of zinc phosphate against steel corrosion beneath the damaged coating.

Personalized Health Monitoring Systems: Integrating Wearable and AI

The integration of wearable technologies and artificial intelligence (AI) has revolutionized healthcare, enabling advanced personal health monitoring systems. This article explores the transformative impact of wearable technologies and AI on healthcare, highlighting the development and theoretical application of the Integrated Personal Health Monitoring System (IPHMS). By integrating data from various wearable devices, such as smartphones, Apple Watches, and Oura Rings, the IPHMS framework aims to revolutionize personal health monitoring through real-time alerts, comprehensive tracking, and personalized insights. Despite its potential, the practical implementation faces challenges, including data privacy, system interoperability, and scalability. The evolution of healthcare technology from traditional methods to AI-enhanced wearables underscores a significant advancement towards personalized care, necessitating further research and innovation to address existing limitations and fully realize the benefits of such integrated health monitoring systems.

Automatic Monitoring System for 3-D Deformation of Crustal Fault Based on Laser and Machine Vision

An automatic monitoring method of the 3-D deformation is presented for crustal fault based on laser and machine vision. The laser source and screen are independently set up in the headwall and footwall, the collimated laser beam creates a circular spot on the screen, meanwhile, the industrial camera captures the tiny deformation of the crustal fault by monitoring the change of the spot position. This method significantly reduces the cost of equipment and labor, provides daily sampling to ensure high continuity of data. A prototype of the automatic monitoring system is developed, and a repeatability test indicates that the error of spot jitter can be minimized by consecutive samples. Meanwhile, the environmental correction model is determined to ensure that environmental changes do not disturb the system. Furthermore, the automatic monitoring system has been applied at the deformation monitoring station(KJX02) of China Beishan underground research laboratory, where continuous deformation monitoring is underway.

Design of IoT-based Volatile Organic Compounds Monitoring System

Volatile organic compounds(VOC)gas detection devices based on semiconductor sensors have become a common method due to their low cost,simple principle,and small size.However,with the continuous development of materials science,various new materials have been applied in the fabrication of gas sensors,but these new materials have more stringent requirements for operating temperature,which cannot be met by existing sensor modules on the market.Therefore,this paper proposes a temperature-adjustable sensor module and designs an environmental monitoring system based on the STM32F103RET6 microprocessor.This system primarily utilizes multiple semiconductor gas sensors to monitor and record the concentrations of various harmful gases in different environments.It can also monitor real-time temperature,humidity,and latitude and longitude in the current environment,and upload the data to the Internet of Things via 4G communication.This system has the advantages of small size,portability,and low cost.Experimental results show that the sensor module can achieve precise control of operating temperature to a certain extent,with an average temperature error of approximately 3%.The monitoring system demonstrates a certain level of accuracy in detecting target gases and can promptly upload the data to a cloud platform for storage and processing.A comparison with professional testing equipment shows that the sensitivity curves of each sensor exhibit similarity.This study provides engineering and technical references for the application of VOC gas sensors.

Research on a Comprehensive Monitoring System for Tunnel Operation based on the Internet of Things and Artificial Intelligence Identification Technology

This article proposes a comprehensive monitoring system for tunnel operation to address the risks associated with tunnel operations.These risks include safety control risks,increased traffic flow,extreme weather events,and movement of tectonic plates.The proposed system is based on the Internet of Things and artificial intelligence identification technology.The monitoring system will cover various aspects of tunnel operations,such as the slope of the entrance,the structural safety of the cave body,toxic and harmful gases that may appear during operation,excessively high and low-temperature humidity,poor illumination,water leakage or road water accumulation caused by extreme weather,combustion and smoke caused by fires,and more.The system will enable comprehensive monitoring and early warning of fire protection systems,accident vehicles,and overheating vehicles.This will effectively improve safety during tunnel operation.

Design of Intelligent Window Automatic Monitoring System Based on Microcontroller Control

To ensure the safety of residents’lives and property by using automatic opening and closing of ordinary windows,this article designs an intelligent window automatic monitoring system.The article proposes a software and hardware design scheme for the system,which comprises a microcontroller control module,temperature and humidity detection module,harmful gas detection module,rainfall detection module,human thermal radiation induction module,Organic Light-Emitting Diode(OLED)display module,stepper motor drive module,Wi-Fi communication module,etc.Users use this system to monitor environmental data such as temperature,humidity,rainfall,harmful gas concentrations,and human health.Users can control the opening and closing of windows through manual,microcontroller,and mobile application(app)remote methods,providing users with a more convenient,comfortable,and safe living environment.

Research on Smart Energy Monitoring and Management System Based on Digital Twin Technology

Smart energy monitoring and management system lays a foundation for the application and development of smart energy. However, in recent years, the work efficiency of smart energy development enterprises has generally been low, and there is an urgent need to improve the application efficiency, resilience and sustainability of smart energy monitoring and management system. Digital twin technology provides a data-centric solution to improve smart energy monitoring and management system, bringing an opportunity to transform passive infrastructure assets into data-centric systems. This paper expounds on the concept and key technologies of digital twin, and designs a smart energy monitoring and management system based on digital twin technology, which has dual significance for promoting the development of smart energy field and promoting the application of digital twin.

Operational modal identification of suspension bridge based on structural health monitoring system

An output-only modal identification method by a combination use of the peak-picking method and the cross spectrum methods are presented. Meanwhile, a novel mode shape optimum method of the deck is proposed. The methods are applied to the operational modal identification system of the Runyang Suspension Bridge, which can be used to obtain the modal parameters of the bridge from out-only data sets collected by its structural health monitoring system （SHMS）. As an example, the vibration response data of the deck, cable and tower recorded during typhoon Matsa excitation are used to illustrate the program application. Some of the modal frequencies observed from deck vibration responses are also found in the vibration responses of the cable and the tower. The results show that some modal shapes of the deck are strongly coupled with the cable and the tower. By comparing the identification results from the operational modal system with those from field measurements, a good agreement between them is achieved, but some modal frequencies identified from the operational modal identification system （OMIS）, such as L1 and L2, obviously decrease compared with those from the field measurements.

Monitoring and Assessment System of Agricultural Drought Based on GIS Technology

[Objective] The research aimed to simplify the operating process of agricultural drought monitoring and assessment product,and improve fine level of monitoring and assessment map.[Method] By comprehensively using GIS and mathematics,meteorology,management science,computer science,the monitoring and assessment of drought were as the core,the monitoring and assessment system of agricultural drought based on GIS technology was studied.[Result] The drought in Guangxi on November 4,2006 was monitored by using the system,and the actual situation was used to test.The result proved that the good monitoring effect was obtained.[Conclusion] The monitoring and assessment system of agricultural drought based on GIS realized the organic combination of GIS and professional monitoring,assessment model.The flexible HCI interface and visualization expression were provided.The monitoring and assessment function of agricultural drought was realized.It had the good practicality and advancement.

DEBRIS MONITORING AND ANALYZING SYSTEM (DMAS) AND ITS APPLICATION IN AEROENGINE

By inspecting and analyzing the debris, which is the most direct and important information units in the lubricating oil, we can monitor the machine condition to predict its failure. The debris monitoring and analyzing system (DMAS) is developed from the traditional iron spectrum technology, and has such characteristics as ease for debris separating, forecasting machine failure automatically and accurately in time and so on. The fundamental theory, components and its application in aeroengine health monitoring of DMAS are presented.

Embedded Remote Monitoring System of Agricultural Environment Based on DSP

Agricultural environmental remote monitoring,data collection and network transmission are the development directions of modern agriculture.The embedded video remote monitoring system is designed with DSP processor DM642,which can collect the video signal of agricultural environment and biological information,as well as complete the extraction of video signal and network transmission.This system can be applied to the agro-ecological and environmental resources monitoring,agricultural disaster monitoring and warning and other digital agricultures.

Sea water temperature auto-monitoring system based on general packet radio service (GPRS)

This paper introduces the design and implementation of sea-water temperature auto-monitoring system based on General Packet Radio Service （GPRS）. This system integrates modern wireless communication technology, the signal gathering technology and computer network technology. MSC1210 microcontroller is used in data collection device in order to make system accurate and fast. In addition, wireless and Internet technologies are used for transferring and displaying collected field data. A prototype system has been completed and tested in field trials. The results proved the feasibility and usefulness of this system for monitoring the temperature. By using this system, a lot of resources and money can be saved.

AN INTELLIGENT TOOL CONDITION MONITORING SYSTEM USING FUZZY NEURAL NETWORKS

Reliable on line cutting tool conditioning monitoring is an essential feature of automatic machine tool and flexible manufacturing system (FMS) and computer integrated manufacturing system (CIMS). Recently artificial neural networks (ANNs) are used for this purpose in conjunction with suitable sensory systems. The present work in Norwegian University of Science and Technology (NTNU) uses back propagation neural networks (BP) and fuzzy neural networks (FNN) to process the cutting tool state data measured with force and acoustic emission (AE) sensors, and implements a valuable on line tool condition monitoring system using the ANNs. Different ANN structures are designed and investigated to estimate the tool wear state based on the fusion of acoustic emission and force signals. Finally, four case studies are introduced for the sensing and ANN processing of the tool wear states and the failures of the tool with practical experiment examples. The results indicate that a tool wear identification system can be achieved using the sensors integration with ANNs, and that ANNs provide a very effective method of implementing sensor integration for on line monitoring of tool wear states and abnormalities.

Monitoring System for Field Soil Water Content Based on the Wireless Sensor Network

[Objective] To water content monitoring study the application of wireless sensor network in field so and to discuss the methods for solving the problems of low sampling rate, high cost and poor real-time in actual monitoring. [Method] The architecture of wireless sensor network, network nodes, hardware design as well as principle for the program structure of software operating system and corresponding parameters were analyzed to illustrate the characteristics of monitoring system for field soil water content based on wireless sensor network, and the advantages in application of this system. [Result] Sensor nodes could correctly collect and transmit soil water content, realize stable data transmission of soil water content, indicating that wireless sensor network is suitable for real-time monitoring of field soil water content. [Conclusion] This study indicates that wireless sensor network possesses a widely application foreground in the development of agriculture.