Monitoring Server Research Articles

Worker Presence Monitoring in Complex Workplaces Using BLE Beacon-Assisted Multi-Hop IoT Networks Powered by ESP-NOW

The increasing adoption of Internet of Things (IoT) technologies has facilitated the creation of advanced applications in various industries, notably in complex workplaces where safety and efficiency are paramount. This paper addresses the challenge of monitoring worker presence in vast workplaces such as shipyards, large factories, warehouses, and other construction sites due to a lack of traditional network infrastructure. In this context, we developed a novel system integrating Bluetooth Low Energy (BLE) beacons with multi-hop IoT networks by using the ESP-NOW communications protocol, first introduced by Espressif Systems in 2017 as part of its ESP8266 and ESP32 platforms. ESP-NOW is designed for peer-to-peer communication between devices without the need for a WiFi router, making it ideal for environments where traditional network infrastructure is limited or nonexistent. By leveraging the BLE beacons, the system provides real-time presence data of workers to enhance safety protocols. ESP-NOW, a low-power communications protocol, enables efficient, low-latency communication across extended ranges, making it suitable for complex environments. Utilizing ESP-NOW, the multi-hop IoT network architecture ensures extensive coverage by deploying multiple relay nodes to transmit data across large areas without Internet connectivity, effectively overcoming the spatial challenges of complex workplaces. In addition, the Message Queuing Telemetry Transport (MQTT) protocol is used for robust and efficient data transmission, connecting edge devices to a central Node-RED server for real-time remote monitoring. Moreover, experimental results demonstrate the system’s ability to maintain robust communication with minimal latency and zero packet loss, enhancing worker safety and operational efficiency in large, complex environments. Furthermore, the developed system enhances worker safety by enabling immediate identification during emergencies and by proactively identifying hazardous situations to prevent accidents.

Implementation of Solar Panels as an Alternative to Electric Power Used in WiFi-based Freezer Box Temperature Monitoring System (Case Study of NN Frozen Food Wajak)

A freezer box temperature monitoring system using solar panels as alternative power is an important technology to ensure the quality of stored products. This research develops a WiFi-based temperature monitoring system that uses a DS18B20 temperature sensor, a PZEM-004T digital sensor, and an ESP8266 module to read and send real-time data to a website platform. Data is collected through a temperature sensor connected to the ESP8266 microcontroller, then displayed on the LCD screen and uploaded to the server for further monitoring via WiFi connection. The results show that this system successfully maintains the freezer box temperature at optimal conditions with an average temperature value of -24.82°C and a temperature range ranging from -28.81°C to -19.63°C. The voltage values are in the range of 197.10 V - 218.70 V, current between 0.02 A - 1.03 A, and power between 158 W - 186.80 W.

Secure-by-Design Real-Time Internet of Medical Things Architecture: e-Health Population Monitoring (RTPM)

The healthcare sector has undergone a profound transformation, owing to the influential role played by Internet of Medical Things (IoMT) technology. However, there are substantial concerns over these devices’ security and privacy-preserving mechanisms. The current literature on IoMT tends to focus on specific security features, rather than wholistic security concerning Confidentiality, Integrity, and Availability (CIA Triad), and the solutions are generally simulated and not tested in a real-world network. The proposed innovative solution is known as Secure-by-Design Real-Time IoMT Architecture for e-Health Population Monitoring (RTPM) and it can manage keys at both ends (IoMT device and IoMT server) to maintain high privacy standards and trust during the monitoring process and enable the IoMT devices to run safely and independently even if the server is compromised. However, the session keys are controlled by the trusted IoMT server to lighten the IoMT devices’ overheads, and the session keys are securely exchanged between the client system and the monitoring server. The proposed RTPM focuses on addressing the major security requirements for an IoMT system, i.e., the CIA Triad, and conducts device authentication, protects from Denial of Service (DoS) and Distributed Denial of Service (DDoS) attacks, and prevents non-repudiation attacks in real time. A self-healing solution during the network failure of live e-health monitoring is also incorporated in RTPM. The robustness and stress of the system are tested with different data types and by capturing live network traffic. The system’s performance is analysed using different security algorithms with different key sizes of RSA (1024 to 8192 bits), AES (128 to 256 bits), and SHA (256 bits) to support a resource-constraint-powered system when integrating with resource-demanding secure parameters and features. In the future, other security features like intrusion detection and prevention and the user’s experience and trust level of such a system will be tested.

Towards early forest fire detection and prevention using AI-powered drones and the IoT

Wildfires are a significant natural hazard, resulting in financial losses, human deaths, and environmental damage. Due to the rising severity and frequency of wildfires, wildfire management and detection have recently received increased attention worldwide. Monitoring potential risk areas and early fire detection are critical factors for shortening the reaction time and reducing the potential damage. Conventional wildfire detection techniques like satellite imaging and remote camera-based sensing need more latency and low reliability. To tackle these limitations, this paper proposes a novel airborne UAV-based IoT (UIoT) system for wildfire sensing, detection, and extinguishing. It presents the design of low-cost and low-maintenance fire-detecting IoT nodes for large-scale deployment. It also proposes, investigates, and reports on several connectivity architectures using the LoRaWAN protocol for UIoT systems. We geolocate forest trees in a terrain-mapping exercise for precise fire localization. We then deploy an autonomous drone with a visual camera that utilizes our novel classification network to detect the presence of fire followed by fire detection and particle filter-based tracking to center fire at the center of the frame. We use a cloud back-end server for monitoring, analysis, and reporting. Our results show that our low-cost and long-range IoT nodes accurately detect fire within 1-5 min after fire ignition. Our fire classification network achieved an accuracy of 99.46% and a mean average precision of 99.64%. Numerical results suggest that the proposed UAV-IoT-based fire classification offers a fast and reliable wildfire recognition and extinguishing solution while minimizing power consumption and increasing the battery lifespan.

ВИКОРИСТАННЯ ВІДДАЛЕНОГО МОНІТОРИНГУ ДЛЯ ПІДВИЩЕННЯ ЯКОСТІ ТА ЕФЕКТИВНОСТІ У ВИРОБНИЧОМУ СЕРЕДОВИЩІ

The article thoroughly examines the challenges associated with monitoring computer networks and servers in the context of rapid technological advancements and increasing complexity. The effective management and monitoring of networks and servers have become critically important due to the growing exchange of data and the need to ensure their continuous operation. The article proposes solutions based on innovative software tools such as Prometheus and Grafana, which provide real-time monitoring and data visualization capabilities to enhance understanding of the state of networks and servers. Traditional monitoring methods, their limitations, and the advantages of the new approach based on Prometheus and Grafana are discussed. Through these tools, network administrators can gain full control over the status and resource utilization of networks and servers, enabling them to promptly address any issues or deviations in their operation. The successful implementation of a monitoring system using these tools is demonstrated, along with an analysis of the prospects for further development of this approach. The methodology of the research is described in detail, including the main tasks of server and network monitoring, as well as the principles of operation of the Prometheus system. A comparison with traditional monitoring methods is conducted to highlight the advantages of the new approach and its importance in the modern information environment. The article also focuses on the possibilities of extending monitoring to other services and devices such as SSH, email, Jenkins, and Kubernetes. The architectural foundation of Prometheus and Grafana is presented, along with methods of their utilization for data visualization and system status notification. This article will serve as a valuable source of information for network administrators, system engineers, and anyone interested in the monitoring and management of information systems in industrial environments.

Smart Fault Detection on Transmission Lines via IoT Technology

In today's society, the reliability of electricity supply is paramount for sustaining essential services and infrastructure. However, power transmission networks, crucial for distributing electricity over vast distances, are vulnerable to faults that can cause equipment damage and service disruptions. Rapid fault detection is crucial to minimize these risks. This paper proposes an innovative IoT-based solution for detecting faults in transmission lines. The system integrates a center-tapped transformer and switches to simulate fault conditions, allowing real-world testing of fault detection mechanisms. Voltage signals from the transmission line are meticulously analyzed using opto-couplers and a micro-controller, which compare these signals with predefined references. Upon fault detection, immediate notifications are displayed on an LCD and transmitted via a WiFi-enabled IoT system for swift action. Furthermore, all data is logged on a central server for comprehensive analysis and ongoing monitoring. This research endeavors to significantly enhance the reliability and efficiency of transmission line operations by implementing advanced fault detection technologies, thereby reinforcing the resilience of electricity supply networks essential for modern society. Key Words: IoT,WiFi Module,Micro-controller,Transmission line.

MOODLE MANUAL UPGRADE METHODOLOGY

This abstract outlines a systematic four-step methodology for upgrading Moodle from version 3.6.5 to 3.9.9. The process begins with comprehensive backup and preparation, followed by the replacement of the Moodle codebase and execution of the upgrade script. Post-upgrade checks are performed to ensure the smooth functioning of core and third-party components. Additionally, the abstract explores the actions and functions of the cron script, emphasizing its role in executing scheduled tasks critical for Moodle's operation.
 Furthermore, the document sheds light on common reasons behind slow Moodle operation and provides practical tips for enhancing system speed. Recommendations include optimizing server resources, database maintenance, strategic caching implementation, and the judicious use of content delivery networks (CDNs). The importance of upgrading PHP and database versions is highlighted, alongside the benefits of disabling unused features and employing server monitoring tools. The abstract emphasizes the significance of staying abreast of Moodle updates for continued performance improvements and bug fixes, offering a holistic guide for upgrading and optimizing Moodle systems.

EFFICIENT PLANT GAS LEAKAGE DETECTION AND MONITORING SYSTEM BASED ON IOT INTEGRATION

In industrial areas, fire breakouts often stem from gas leaks within the surrounding environment. These leaks could be caused by faulty apparatus, inadequate maintenance, or human mistake either during handling or storage of flammable gases. The presence of combustible gases poses a significant risk, as they can ignite easily and escalate into large-scale fires, endangering both personnel and property within the industrial site. This research employs a compact detection device capable of identifying combustible gases like propane, LPG Gas, Carbon Monoxide, butane, and other hazardous gases. The device is designed to identify these gases quickly and accurately, aiding in ensuring safety in various environments such as industrial sites, homes, and workplaces. The leakage detector includes NODEMCU, gas sensors, buzzer, and LCD system. When harmful gases surpass acceptable thresholds, the micro-controller initiates a alerting SMS using Blynk server. The prototype emits a sound alert and illuminates LCDs to indicate the leaking gas. Gas concentration datais sent to Thinkspeak server for easy monitoring by plant personnel.

Deploying Nagios for Service Monitoring and Reporting

NAGIOS is Server Monitoring tool as an important criteria coming to a data center operation and service .Detects all type of network errors or server issues and allowed to monitor the server performance issues by using Nagios. This can be manually and physically monitoring the location of the server and mapping the network interface and network bridge server will be monitor. Count every 10 minutes once the application will be running properly or else store application related bugs in data center. Large organizations always require fast and efficient network monitoring system which reports to the network administrator as soon as a network problem arises. This paper presents an effective and automatic network monitoring system that continuously monitor all the network switches and inform the administrator by E-MAIL or SMS when any of the network switch goes down. An efficient and automatic network monitoring is always required for large organizations like universities, companies and other business sectors where the manual network monitoring is very difficult. Since large organizations have a big network topology, the manual network monitoring causes waste of time to point out problem location.

Improving a procedure of load balancing in distributed IoT systems

The object of this research is the process of load balancing in distributed Internet of Things (IoT) systems. Within this work, a complex of problems related to efficient load distribution has been addressed. The authors conducted an analysis of existing load-balancing approaches and their drawbacks and proposed an enhanced architecture for the MQTT broker. Additionally, methods and algorithms for load balancing were developed based on multi-criteria server monitoring. Furthermore, the authors created a mathematical model to assess the uniformity of load distribution in the system and introduced a corresponding metric – the load distribution coefficient. In order to evaluate the proposed load balancing methods, a series of experiments were conducted, including the simulation of a distributed IoT system with non-deterministic load. The main goal of these experiments was to assess the uniformity of MQTT load distribution by the broker. The results of the experiments confirmed the hypothesis of improved load distribution efficiency through multi-criteria monitoring-based balancing. The utilization of the proposed load-balancing methods allowed for a more efficient utilization of computational resources. It was found that when using the proposed methods, in the case of non-deterministic load in the IoT system, the load distribution coefficient on average exceeded the corresponding indicator of existing methods by 70 %. In addition, the value of this coefficient for the proposed methods remains virtually unchanged throughout the experiment, which is evidence of the stable operation of the system as a whole. The results obtained can be useful in the development of modern IoT systems.

Design of a Temperature Control and Object Motion Detection System in the Server Room Using IOT-Based Wemos D1

Servers play an important role in managing information and managing network traffic within an agency. It contains various types of network devices that must be kept on every day to provide the best service. This leads to the importance of maintaining server presence, such as paying attention to room humidity, regulating temperature and monitoring server room movements to keep it under control. The air temperature in the server room is set within 20 - 25 degrees Celsius with a relative humidity of 40 - 55%. In this context, the concept of the Internet of Things (IoT) emerges as a potential solution by connecting physical objects via the internet. This research designs and builds an IoT-based temperature control and object motion detection system using a DHT22 sensor to measure the temperature in the room and a PIR sensor to detect human movement. Hardware components such as Wemos D1, Buzzer, Relay 2 channel 5v, and others are used to control the system via a smartphone. The software used includes the Arduino IDE. This system aims to monitor and control room temperature and object movement detection systems intelligently, prevent overheating, reduce the risk of loss and combine the advantages of IoT technology to create a temperature control and motion detection system that is responsive to room temperature and the movement of objects in the room.

Real-time Defense Against Cyber Threats: Analyzing Wazuh's Effectiveness in Server Monitoring

Real-time Defense Against Cyber Threats: Analyzing Wazuh's Effectiveness in Server Monitoring

Improvement of the Integral Indicator of the Ecological and Toxicological Assessment of the Danger of the Use of Pesticides in Agriculture and the Creation of an Information System for Their Monitoring

The aim of the work was to assess the ecological and toxicological dangers of pesticides using the value of a complex indicator determined by the calculation method. An integral indicator of the relative ecological and toxicological danger of pesticide use (Hr) is proposed, which allows taking into account the acute oral and chronic toxicity of the pesticide for mammals and its impact on the environment (half-life in soil and chronic toxicity for aquatic organisms), as well as the rate of application of the drug. The computation was performed on fungicides and insecticides that are most commonly used in grain crop cultivation and approved to be applied in the Russian Federation. The research was carried out in 2022–2023. The results showed that the determined indicator takes values from 0.02 for the fungicide benomyl to 26950 for the insecticide chlorpyrifos. Pesticides were ranked according to the Hr index, and four hazard groups were identified, as well as the main factors that determine them. The first hazard group should include drugs with a Hr greater than 1000; the second hazard group—with Hr from 100 to 1000; the third—with Hr from 1 to 100; and the fourth—with Hr less than 1. The first group includes pesticides with multiple adverse safety profiles, such as chlorpyrifos. The second group includes insecticides fipronil, lambda-cyhalothrin, gamma-cyhalothrin, imidacloprid and the fungicide flutriafol. The indicator can be used for agro-ecological substantiation of the choice of pesticides for the treatment of agricultural crops and for the selection of priority pesticides for regular monitoring of their content in the environment—primarily the first and second hazard groups. It can be performed remotely by appropriate detectors and sensors. All data about farm pollution can be monitored using an information server monitoring system, the architecture of which has been proposed.

Implementation of Enhanced Spray Routing Protocol for VDTN On Surabaya Smart City Scenario

The application of smart-city, which promises better city management in helping to improve people's quality of life, is still inhibited due to the high cost of infrastructure investment. In several Smart Cities, it takes at least $ 30 - 40 billion to convert a conventional town into a smart city, including for data collection infrastructure. Alternatively, low-power wide-area networks (LPWANs) could be considered, but they need more bandwidth to serve data transmission in a smart city. Vehicle Delay Tolerant Network (VDTN) is one part of DTN that employs vehicles as a communication infrastructure that allows communication in challenging conditions and could make it an alternative network for Data Collection in a Smart City. This paper proposes a Surabaya Smart City scenario with VDTN as data collection. The scenario consists of 40 wireless sensors and 50 to 200 vehicles (car and bus) with five Road Side Units that forward data from the sensor to the monitoring server. Furthermore, to increase the VDTN performance, we improve our proposed routing protocol, Spray and Hop Distance (SNHD), with two sprays method (Adaptive and Simple) and data collection support from multiple sources and destinations. The evaluation was carried out using a simulation-based comparison with an increase in the number of vehicles to determine the impact of vehicle density on data collection performance in terms of delivery probability, latency average, and overhead ratio. Based on the simulation results, the simple spray method in SNHD and A-SNHD outperformed the well-known VDTN routing protocol, i.e., Epidemic and Spray and Wait. Furthermore, when the number of cars increases from 50 to 200, the performance of VDTN does not increase significantly as the density of the network increases. It means that VDTN only requires a small number of vehicles to be used as a low-cost alternative network for smart cities.
 

An Efficient and Privacy-Preserving Information Reporting Framework for Traffic Monitoring in Vehicular Networks

Traffic monitoring services show great potential for improving traffic efficiency in vehicular networks. With the assistance of 5G innovation, vehicles can report information such as driving misbehavior and traffic status to the traffic monitoring server which then returns feedback to the network to enhance the efficiency of traffic management. However, some challenging issues in information reporting need to be addressed first. Trivial reported information significantly increases the workload of the server. Moreover, a server is difficult to distinguish the truth of reported messages. As a result, the server is incapable of returning immediate feedback to the network, thereby reducing the quality of traffic services. Meanwhile, uploading location-based information to the server exposes vehicles' privacy. Although some existing techniques such as trust management benefit information reporting, a complete framework is still missing. In this paper, we propose an information reporting framework for solving both efficiency and privacy issues. Specifically, messages are probabilistically reported to the server depending on their importance. Furthermore, the DAG-based blockchain ensures that messages reported for a specific event are all gathered in the same ledger. We also present a scheme based on the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">geo-indistinguishability</i> to protect the location privacy of vehicles. Extensive experiments demonstrate that the proposed framework preserves the location privacy of vehicles and achieves efficiency with acceptable overheads.

RANCANG BANGUN MONITORING SERVER SYSTEM BERBASIS TERMINAL LINUX DAN WHATSAPP GATEWAY STUDI KASUS: PT. XYZ

This research aims to design a server monitoring system based on a Linux terminal and Whatsapp Gateway for PT. XYZ. The purpose of this system is to monitor server conditions in real-time and provide notification to the admin if there is a problem with the server. The method used in this research is by integrating the Linux terminal application with the Whatsapp Gateway using PHP programming language. The research results show that the server monitoring system&#x0D; based on Linux terminal and Whatsapp Gateway can provide real-time notification to the admin if there is a problem with the server, which can help in identifying and solving problems quickly. Thus, this system can improve efficiency in server monitoring and reduce downtime

An Intelligent Server load balancing based on Multi-criteria decision-making in SDN

In an environment of rising internet usage, it is difficult to manage network traffic while maintaining a high quality of service. In highly trafficked networks, load balancers are crucial for ensuring the quality of service. Although different approaches to load-balancing have been proposed in traditional networks, some of them require manual reconfiguration of the device to accommodate new services due to a lack of programmability. These problems can be solved through the use of software-defined networks. This research paper presents a dynamic load-balancing algorithm for software-defined networks based on server response time and content mapping. The proposed technique dispatches requests to servers based on real-time server loads. This technique comprises three different modules, such as a request classification module, a server monitoring module, and an optimized dynamic load-balancing module using content-based routing. There are a variety of robust mathematical tools to address complex problems that have multiple objectives. Multi-Criteria Decision-Making is one of them. The performance of the proposed scheme has been validated by applying the Weighted Sum Method of the multi-criteria decision-making technique. The proposed method Server load balancing based on Multi-criteria Decision Making[SDLB-MCDM] is compared with different load-balancing schemes such as round robin, random, load-balancing scheme based on server response time [LBBSRT], and An SDN-aided mechanism for web load- balancing based on server statistics [SD-WLB]. The experimental results of SDLB-MCDM show a significant improvement of 58% when weights are equal and 50% when unequal weights are assigned to various QoS parameters in comparison with the ROUND ROBIN, RANDOM, LBBSRT and SD-WLB techniques.

Development and Performance Evaluation of Photovoltaic (PV) Evaluation and Fault Detection System Using Hardware-in-the-Loop Simulation for PV Applications

This paper originally presents a photovoltaic (PV) evaluation and fault detection (PVEFD) system for PV applications based on the Internet of Things (IoT) technology. The PVEFD system consists of an STM32F103C8T6 chip with a 32-bit Arm Cortex-M3 reduced instruction set computer (RISC) and 12-bit resolution analog-to-digital converter (ADC) to measure important parameters of PV applications, such as solar irradiance as well as the back-surface cell temperature, operating voltage, and output current of PV devices. The measured data of irradiance as well as back-surface cell temperature and operating voltage of PV devices are then fed into a built-in PV model in the on-chip Arm Cortex-M3 RISC for hardware-in-the-loop (HIL) simulation to obtain the simulated output current and power of PV devices. The resulting data are transmitted to a cloud server for remote monitoring and automatic warning function through a Raspberry PI 3 module and WiFi network. The simulation results are compared with in-field measurement data from PV modules and displayed on a human-machine interface (HMI) and an Android app. The results of the study illustrated that the proposed system features high accuracy and sufficient confidence. Furthermore, the fault detection function through the built-in HIL simulation function in PV systems was validated. Therefore, the proposed system is a small, compact, and cost-effective HIL-on-chip machine for remote surveillance of PV power systems.

Rancang Bangun Monitoring Server System Berbasis Terminal Linux dan Whatsapp Gateway Studi Kasus: PT. XYZ

This research aims to design a server monitoring system based on Linux terminal and Whatsapp Gateway for PT. XYZ. The purpose of this system is to monitor server condition in real-time and provide notification to the admin if there is a problem with the server. The method used in this research is by integrating the Linux terminal application with the Whatsapp Gateway using PHP programming language. The research results show that the server monitoring system based on Linux terminal and Whatsapp Gateway can provide real-time notification to the admin if there is a problem with the server, which can help in identifying and solving problems quickly. Thus, this system can improve efficiency in server monitoring and reduce downtime

Petri Nets-Based Modeling Solution for Cyber–Physical Product Control Considering Scheduling, Deployment, and Data-Driven Monitoring

For a complex electromechanical product that is a cyber–physical system (CPS), its dynamic behaviors are embodied in the closed-loop control between the logic process in its cyber component and actual actuators/sensors in its physical component, and thus, a well-defined model of the control is important to create a digital twin that acts as much like the real machine as possible. This article proposes a Petri nets (PNs)-based modeling solution that employs hybrid PNs (HPNs) for physics and system of sequential systems with shared resources (S4R) nets for logic in building a hierarchical control model. We also present PNs technologies for implementing a smooth transition and bidirectional mapping from the virtual prototype to the real machine. These technologies involve a PNs integration of a reinforcement learning (RL) method for generating a workflow scheduling agent in design, an extension of PNs definitions that is compatible with the microcontroller for easy deployment in manufacturing, and an architecture of PNs execution recording for data-driven monitoring in service. A software kit is provided for the solution that includes an integrated development environment of PNs, tools for quickly building a virtual prototype, and a monitor server for remote data-driven monitoring. This solution is successfully applied in the development of a typical cyber–physical product case, namely, the chemiluminescence immunoassay (CLIA) analyzer.