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Real-time health monitoring and data collection are possible now due to the introduction of Internet of Things (IoT) in modern healthcare systems. Continuous monitoring enables healthcare providers to find and treat potential health problems early, tailor treatment plans specific to the individual patients, and make better clinical decisions resulting in a higher quality of care. From the benefits of integrating IoT in healthcare to security issues being raised when data is collected or transmitted (as health information becomes a sensitive resource). Patient's health information is very confidential and secrecy, any act that disclosed this data in the wrong way can have more implications than just patient identity thefts and financial fraudulence. In this study, we introduce that in order to solve the security and privacy issues of IoT devices in healthcare systems; we present Block chain-based Security-enhanced Public Key Infrastructure (PKI). The solution integrates the decentralized component of blockchain with its automated and standardized functionality for processing all actions afterwards, which allows such a data access as never before. This is a unique feature of blockchain: once data has been entered onto the ledger, it cannot be changed or deleted - meaning that an irrevocable record exists for each transaction. These provide future IoT devices with medical data that remain compliant keeping your health information sanitary. The other advantage of this decentralized solution is that it allows data to be accessed and stored globally, thus improving the availability and robustness of all components in case anyone fails. The Public Key Infrastructure (PKI) on an already existing blockchain platform, this only makes its security even more solid. Our solution assigns the reliability of safety and encrypted interaction among different section in our healthcare infrastructure through PKI cryptographic keys with digital certificates. Additionally, the proposed blockchain PKI improves security while addressing scalability and interoperability challenges that traditional centralized systems cannot solve, all without relying on an expensive third-party certifying authority. [ABSTRACT FROM AUTHOR]

This research proposes an IoT-based system for classifying plant suitability using pH data and soil humidity parameters. The system utilizes Run-Length Encoding (RLE) to compress sensor data, which is transmitted to a database server via the Esp8266 module. A Multilayer Perceptron (MLP) algorithm is employed to classify the data, achieving an accuracy of 0.82 with only two parameters. The classification results are displayed on a website, providing real-time recommendations for farmers. The system's performance is evaluated using a dataset from Kaggle. The Kaggle dataset contains 2200 instances for 22 different plants and the results show that the proposed system can effectively classify plant suitability based on environmental factors. This research contributes to the development of IoT-based recommendation systems for precision agriculture, and future studies can build upon this work to improve accuracy and quality.

Copyright of Informatics Control Measurement in Economy & Environment Protection / Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska is the property of Lublin University of Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Summary The wavelet transform (WT) is a widely used technique for compressing images in the Internet of Things (IoT). However, its compression ratio (CR) needs further improvement when used for IoTs with low communication rates. To address this issue, we propose a lightweight image compression method that combines the WT and number theory transform (NTT). The simulations demonstrate that the proposed method surpasses traditional compression methods in terms of achieving a good balance between CR, image recovery quality, and complexity. Therefore, it is better suited for IoT applications with low transmission rate requirements. [ABSTRACT FROM AUTHOR]

This study proposes a method based on Convolutional Neural Network (CNN) for automated detection of weed in color image format. The image is captured and transmitted to the Internet of Thing (IoT) server following an HTTP request made through the internet which is made available using the GSM based modem connection. The IoT Server save the image inside server drive and the results are displayed on the smartphone (Vision app). The results show that carrot and weed detection can be monitored accurately. The results of the study are expected to provide assistance to farmers in supporting smart farming technology in Indonesia.

This study presents a conceptual design of an Internet of Things (IoT) communication system for monitoring power generation systems in Colombian Non-Interconnected Zones (NIZs), which lack IoT connectivity due to complex geographical factors. The proposed system aims to ensure the proper operation and energy efficiency of off-grid systems while tracking the variables that influence their performance.The methods used in this study include identifying the needs of such a system, identifying requirements, obtaining technical specifications, and developing a conceptual design. The study also analyses and compares various technologies, including Wi-Fi, Bluetooth, LoRa and ZigBee, to determine which ones are best suited for IoT system design.The conceptual design of the proposed IoT monitoring system considers the geographical, communication and coverage characteristics of the NIZs and the technical characteristics of the energy projects to provide a complete functional system that can connect approximately 2 million people located in these isolated and vulnerable zones. Finally, the defined system can serve as a precedent for building prototypes in various NIZs, and research on IoT technologies suitable for NIZs can help us seek the technologies that are most suitable for these areas. Depending on the application and conditions of the energy project, the most appropriate technology can be determined on a case-by-case basis.

Internet of Things (IoT) is a new revolution of the Internet, which can be thought of as an uprising expansion of internet services. IoT is defined in many different ways. It covers many areas of life, including houses, cities, automobiles, and roads. It also includes devices that track people's behavior and utilize the information gathered for push services. Any object may access the web over a wired or wireless network with the IoT. In addition to authentication and security, extensive research and development have gone into energy awareness. Mobile Internet of Things (MIoT) is the following stage in this situation. Mobile data collecting, data analysis, energy management, security and privacy, and the provision of IoT services are some issues arising when using MIoT. So, this paper proposed an energy-aware technique for resource allocation in MIoT. Due to this problem's NP-hard nature, a new approach is suggested to reduce the network's energy consumption and end-to-end delay in MIoT using selfish node ranking and ant colony optimization algorithms. The proposed method is compared to Whale Optimization Algorithm (WOA) and Task Priority-based Resource Allocation (TPRA) algorithms. The findings show the network's substantial changes in energy consumption and end-to-end delay using the proposed method. The findings of the current work are significant for academics and offer insights into upcoming study areas in this subject. [ABSTRACT FROM AUTHOR]

This paper presents the design and characterization of a compact dual-band microstrip antenna for GPS and long range (LoRa) internet of thing (IoT) applications. The antenna operates at 868 MHz and 1.57 GHz and has a gain of 3.35 dBi and 5.08 dBi, respectively. The antenna design is optimized using CST microwave studio software (MWS®), and both simulation and measurement results are in close agreement. The antenna features a directional E-plane and omnidirectional H-plane radiation pattern in each band of operation. The proposed antenna's compact size and dual-band capability make it suitable for IoT applications that require GPS and LoRa communication in a small form factor. The results presented in this paper demonstrate the feasibility and effectiveness of the proposed antenna design. [ABSTRACT FROM AUTHOR]

Information systems are currently developing very rapidly, and this is inseparable from the role of internet of things (IoT) technology, especially in the world of telemedicine. MitApp is an open-source application that can be used to monitor electrocardiogram (ECG) signals in real-time. The aim of this study is to develop an IoT-based ECG signal monitoring system that utilizes the MitApp application to detect abnormal ECG signals that are characterized by symptoms of cardiac arrhythmias. To process ECG signal data obtained from lead electrode results, the research method utilizes Arduino Uno as a microcontroller. The result is then displayed on the thin film transistor (TFT) layer using the Nextion module. The ESP32 module is used as a Wi-Fi module to send data to the MitApp app on a smartphone. The results showed that the results of the comparison test of ECG signal module data with ECG simulator tools with beats per minute values of 60, 80, 100, 120, and 140 obtained an error rate of <0.05. Based on these results, there is potential to develop this feature and integrate the system with the patient management system to improve the effectiveness of remote monitoring. [ABSTRACT FROM AUTHOR]

With the development of IoT applications, machine learning dramatically improves the utility of variable IoT systems such as autonomous driving. Although the pretrain-finetune framework can cope well with data heterogeneity in complex IoT scenarios, the data collected by sensors often contain unexpected noisy data, e.g., out-of-distribution (OOD) data, which leads to the reduced performance of fine-tuned models. To resolve the problem, this paper proposes MuGAN, a method that can mitigate the side-effect of OOD data via the generative adversarial network (GAN)-based machine unlearning. MuGAN follows a straightforward but effective idea to mitigate the performance loss caused by OOD data, i.e., “flashbacking” the model to the condition where OOD data are excluded from model training. To achieve the goal, we design an adversarial game, where a discriminator is trained to identify whether a sample belongs to the training set by observing the confidence score. Meanwhile, a generator (i.e., the target model) is updated to fool the discriminator into believing that the OOD data are not included in the training set but others do. The experimental results show that benefiting from the high unlearning rate (more than 90%) and retention rate (99%), MuGAN succeeds in lowering the model performance degradation caused by OOD data from 5.88% to 0.8%. [ABSTRACT FROM AUTHOR]

Healthcare telemonitoring has emerged as a promising approach to remotely monitor patients remotely, enabling timely intervention and personalized care. Internet of things (IoT) device-generated patient data necessitates innovative solutions for intelligent healthcare decision-making, as current methods struggle to provide timely, context-aware, and data-driven recommendations, resulting in suboptimal patient care. This study aims to develop an intelligent decision-making framework for healthcare telemonitoring by leveraging forward-backward chaining and IoT technology. The research focuses on a system using forward-backward chaining algorithms to analyze real-time patient data from IoT devices. It utilizes machine learning models to adapt to changing conditions and refine decision-making, demonstrating its ability to provide real-time context-aware recommendations. Temperature, blood pressure, oxygen level, and heart rate measurement errors are 2.01%, 1.74 to 2.13%, 0.61%, and 1.45%, respectively. The success rate of early disease diagnosis using an expert system is 81%, with an average application interface responsiveness time of 4.978 s. The integration of IoT data with intelligent decision-making algorithms in healthcare telemonitoring has the potential to revolutionize patient care. However, future work should focus on scalability and interoperability for diverse healthcare settings. [ABSTRACT FROM AUTHOR]

This study proposes the design and development of public light systems integrated with Internet of Things (IoT) applications for smart cities. Smart public lighting systems are designed using LED light sources in combination with a controller based on light intensity and motion sensors to control the brightness in working areas as per standard requirements. The control of smart public lighting systems is designed to operate in three modes: manual, scheduled, and auto modes, which are tested and compared in terms of lighting and power quality. Other functions of IoT, such as air pollution detection, security system-based video surveillance, and warning systems for flood disasters, are integrated into smart public lighting systems. A prototype of the designed smart public lighting system is presented in this paper. The parameters of average illuminance, overall uniformity, and threshold increment were implemented using DIALux software to optimise the luminaire spacing. The results showed that the goal of energy saving could be achieved using the auto mode. Although the automatic mode caused current harmonic distortion to the electrical grid, the harmonic value was less than the specified standard. Furthermore, the precision of IoT system operation was dependent on environmental variations and the reliability of wireless network technology.

The rapid development of wireless communication technology has led to an increasing number of internet of thing (IoT) devices, and the demand for spectrum for these devices and their related applications is also increasing. However, spectrum scarcity has become an increasingly serious problem. Therefore, we introduce a collaborative spectrum sensing (CSS) framework in this paper to identify available spectrum resources so that IoT devices can access them and, meanwhile, avoid causing harmful interference to the normal communication of the primary user (PU). However, in the process of sensing the PUs signal in IoT devices, the issue of sensing time and decision cost (the cost of determining whether the signal state of the PU is correct or incorrect) arises. To this end, we propose a distributed cognitive IoT model, which includes two IoT devices independently using sequential decision rules to detect the PU. On this basis, we define the sensing time and cost functions for IoT devices and formulate an average cost optimization problem in CSS. To solve this problem, we further regard the optimal sensing time problem as a finite horizon problem and solve the threshold of the optimal decision rule by person-by-person optimization (PBPO) methodology and dynamic programming. At last, numerical simulation results demonstrate the correctness of our proposal in terms of the global false alarm and miss detection probability, and it always achieves minimal average cost under various costs of each observation taken and thresholds. [ABSTRACT FROM AUTHOR]

This paper presents an IoT smart building platform with fog and cloud computing capable of performing near real-time predictive analytics in fog nodes. The researchers explained thoroughly the internet of things in smart buildings, the big data analytics, and the fog and cloud computing technologies. They then presented the smart platform, its requirements, and its components. The datasets on which the analytics will be run will be displayed. The linear regression and the support vector regression data mining techniques are presented. Those two machine learning models are implemented with the appropriate techniques, starting by cleaning and preparing the data visualization and uncovering hidden information about the behavior of the smart building appliances using the energy consumption feature. Afterwards, the implementation of two regression models to predict total energy consumption began. On a hospital database, the two techniques' performances are compared and validated. The results achieved are promising and prove the reliability of the IoT smart building platform. [ABSTRACT FROM AUTHOR]

Healthcare and technology have a long history of interaction but eHealth adoption has been delayed due to a lack of infrastructure, capacity, and political will. It is called a health information technology system (HITS) or smart health system (SHS) when healthcare adopts health technology. Customers should expect improved service in terms of efficiency and cost after the system's modifications have been implemented. Exclusively after the COVID-19 pandemic, it was the test case of eHealth system worldwide, but the eHealth system is in its initial stage and facing different kinds of issues. Technology such as cloud computing and IoT enables HITS services to be delivered via the internet securely and scalable. Pay-as-you-go is the basis for this type of eHealth model, which various healthcare industries use to meet present and future demand by utilizing various frameworks. Cloud computing and the internet of things (IoT) are key components of an eHealth system described in this review paper. We also discuss the various parameters that make up this system's structure. After summarizing several research works based on IoT and cloud computing in eHealth, we describe challenges that still limit the efficiency and indicate future prospects for tackling these problems to further increase the development of eHealth systems in the next few years. [ABSTRACT FROM AUTHOR]

The internet of things (IoT) has the potential to significantly impact growth due to the technological revolution, widespread dissemination of information, and emergence of events. Intelligent housing, urban centers, and educational systems are all forms of intelligence. The IoT gs has garnered significant attention from researchers, who claim that this technology will play a pivotal role in determining the future of the Internet, as per the reports of Cisco Inc., in this context, the concept of a smart campus refers to the establishment of a durable and interconnected setting that enhances learning, efficiency, and the overall living experience. Similar to other intelligent environments, the smart campus is susceptible to a variety of risks and threats this situation presents important security-related challenges that have an influence on the advancement of the campus. This article presents an overview of intelligent campuses by emphasizing the primary applications and technologies utilized. It provides an examination and evaluation of the primary security concerns associated with smart campuses, classified based on their respective types and levels of significance, and determines the security requirements, current threats and attacks, and the state of the art in terms of architectural solutions and the prevention of security vulnerabilities. [ABSTRACT FROM AUTHOR]

Abstract. IoT (Internet of Things) technology is currently experiencing very rapid development. Several innovative and creative applications, most IoT-based, have been found. IoT underlies the existence of smart home technology. One of the advantages of smart home technology is that homeowners can control conditions and monitor home security using only one device. Unfortunately, at SMKs Darul Ulum Layoa, Bantaeng, Sulawesi Selatan (South Sulawesi), learning about IoT still needs to be improved. It becomes the basis for why we hold a community service activity. This activity provided understanding and training on the Internet of Things, which 40 teachers and students attended. Pretest and posttest methods are used to determine the activity's success level. Both results were processed using the SPSS (Statistical Package for the Social Sciences) method. SPSS is a statistical software used to perform data analysis, including descriptive and inferential analysis. By utilizing the Wilcoxon Signed Rank Test, an analysis of the data revealed a Z value of -5.026 and a p-value of 0.000. These findings indicate a significant difference between the pretest and posttest groups or a significant increase in scores between the pretest and posttest. Therefore, the intervention had a positive effect on the outcome being measured.

The past few years have witnessed a surge in technological development in all areas of life, and its emergence has led to great changes in human life from primitiveness to controlling the matter through the Internet. Each new technology has an impact on completely changing societies, which led to many changes in concepts and practices. Among the most Types of technology spread and impact on products of all kinds, and it is one of the applications of the fourth industrial revolution, we find that IOT works on making the whole world connected to each other through communication and information exchange through the Internet connection to make all products able to communicate with each other, through Four main pillars are (Things - People Users - Connectivity - Data Processing), and therefore it erases the line between the digital and physical world, through IOT the world will become as a smart product in all its aspects, it will also be able to make some decisions and this As a result of the data stored on its own cloud, there are many products that use the concept of IOT and are no longer limited to the concepts of smart cities and cities. Smart Homes but also include Wearable Devices, Health Care applications, Transportation, Education, Smart Retail Stores, and Mobility. Which adapts to the needs of the user, and in light of these changes, it has become important for the designer to take into account this technology and the extent of its impact on the product life cycle and on the process of designing and developing the product.

Blockchain technology is at the peak of hype and contemporary research area across the world. It is a distributed ledger that keeps records of transactions with verifiable and immutable structures and continuously grows with the new block of transactions. Blockchain provides better transparency, enhanced security and privacy, and true traceability over the traditional approaches. Due to its advanced and secure features, it is being used in various fields such as trade finance, digital transactions, the Internet of Things (IoT), the healthcare industry, and energy sector. Blockchain technology has a great impact in all its applied fields with the prominent features of privacy and reliability of data and transactions. This survey intends to present the architecture of blockchain, its potential applications, and practices in different domains other than cryptocurrency along with the platform of blockchain. This paper will explore some potential benefits of blockchain and some future directions and open challenges that are expected to come in future research. [ABSTRACT FROM AUTHOR]

Agents are currently being discussed in nearly every domain of science and engineering. Through the ut ilization of IoT and agentbased systems, remote consultations and virtual doctors can provide essential healthcare services by analyzing patient data and medical history. The purpose of this paper is provide an analysis the requirements for multi-agent systems in patient-centered health consultancy services in Kenya. It focuses on various agent types, including hardware, hospital, human, software, database/storage, and technological/framework agents. For hardware, computers, laptops, and mobile devices need specific processing power, memory, network connectivity, storage, and security. Medical equipment must prioritize accuracy, reliability, integration with records, and regulatory compliance. Networking requires high-speed internet, security, and redundancy. Hospital agents offer comprehensive inpatient and outpatient care, categorized into general, mental health, and specialized hospitals. Human agents, like medical specialists, IT professionals, and administrators, play essential roles in healthcare consultancy. Software agents encompass Electronic Health Records (EHRs), Clinical Decision Support Systems (CDSS), Telemedicine platforms, and more. Database/storage agents include EHRs, Health Information Exchange (HIE) systems, and data encryption. Technological/framework agents involve health information systems, telemedicine platforms, decision support systems, and health data analytics frameworks. These agents enable efficient data management, remote care, evidence-based decisions, and secure data exchange. [ABSTRACT FROM AUTHOR]

The monitoring performance of the photovoltaic system in real time is required for estimation and optimization purposes. This monitoring system has been the subject of extensive research, but in general it employs costly commercial software and as well as other license-based software. This paper discusses the design of a photovoltaic parameter monitoring system that uses Internet of Things technology to monitor in real time. This software is intended to be as interactive as possible in order to display all measurement data in the form of graphical according to a user-specified time interval. The constructed system is tested to display the measurement parameters of the fixed and dual axis solar tracker. The test results indicate that the system can display data in real time. Every data shown is accessible from any location and at any time, so long as the device being used is connected to the Internet. This system obviously can be applied and developed for an internet of thing-based photovoltaic parameter monitoring system to facilitate system estimation and optimization. [ABSTRACT FROM AUTHOR]

Along with the development of science and technology, especially internet of things (IOT), IOT-related products increasingly contribute to improving people’s life. Among those products, it is impossible not to mention smarts city, internet of Vehicle devices and especially smart home, which are usually voice controlled. Therefore, voice processing technology is also in need of improvement. The article mainly focuses on processing human voice independently of text. In particular, Convolutional network (CNN) and Support Vector Machine (SVM) will be integrated to create Feature Building Machine. SVMs are often used in voice and image classification, which accordingly is a critical and swift data sorter. The article analyzes the advantages of the combination Deep Neural Network (DNN) and SVMs in voice recognition and is the foundation to develop devices for smart home. The experimental results, which was used in the standard Voxceleb database, demonstrate the superiority in sound recognition compared to traditional i-vector methods or other CNN methods.

Physical objects that may communicate with one another are referred to “things” throughout the Internet of Things (IoT) concept. It introduces a variety of services and activities that are both available, trustworthy and essential for human life. The IoT necessitates multifaceted security measures that prioritize communication protected by confidentiality, integrity and authentication services; data inside sensor nodes are encrypted and the network is secured against interruptions and attacks. As a result, the issue of communication security in an IoT network needs to be solved. Even though the IoT network is protected by encryption and authentication, cyber-attacks are still possible. Consequently, it’s crucial to have an intrusion detection system (IDS) technology. In this paper, common and potential security threats to the IoT environment are explored. Then, based on evaluating and contrasting recent studies in the field of IoT intrusion detection, a review regarding the IoT IDSs is offered with regard to the methodologies, datasets and machine learning (ML) algorithms. In This study, the strengths and limitations of recent IoT intrusion detection techniques are determined, recent datasets collected from real or simulated IoT environment are explored, high-performing ML methods are discovered, and the gap in recent studies is identified.

In general, plant growth will be disrupted if the environmental temperature is not suitable, even the plants will be damaged, which can cause a decrease in quality and quantity. Problems that often occur and are difficult to avoid include temperature and humidity conditions on agricultural land. Therefore it is necessary to do handling to be able to minimize the occurrence of damage that can occur in the land caused by environmental influences. This study aims to design a temperature and humidity monitoring system based on the Internet of Things (IoT). The research was carried out by designing electronic circuits from monitoring systems, hardware, software, and testing the systems that had been made. Technology supported by the use of DHT22 sensors can read temperature and humidity data in real time. Based on the research results, it was found that the DHT22 sensor used worked with the best accuracy on day 21 with an error percentage of 0% and the worst accuracy occurred on day 31 with an error percentage of 18.5%.

Pada era revolusi industri 4.0 saat ini, industri akan memasuki dunia virtual serta penggunaan mesin-mesin automasi yang terintegrasi dengan internet sehingga efek yang ditimbulkan dari penerapan teknologi ini adalah meningkatnya efisiensi produksi dan terjadi peningkatan produktivitas serta daya saing. Pada bidang olahraga tenis lapangan, teknologi automasi yang terintegrasi dengan internet ini belum banyak diterapkan. Salah satu penggunaan teknologi yang terintegrasi dengan internet ini dapat diaplikasikan kedalam sebuah alat pelontar bola tenis lapangan sehingga memudahkan atlet dan pelatih tenis lapangan dalam berlatih. Dalam penelitian ini, merancang sebuah robot pelontar bola tenis lapangan berbasis Internet of Thing (IoT) yang bertujuan untuk memberikan kemudahan dan efisiensi untuk para atlet dan pelatih dalam berlatih. Pembuatan alat ini terdiri dari perangkat keras seperti Arduino Mega2560, ESP32, motor DC, driver BTS7960, display LCD 16x2, I2C, sensor IR, selonoid, sensor ultrasonik, push button, dan joystick modul. Adapun perangkat lunak (software) yang digunakan yaitu Arduino IDE dan Blynk. Hasil dari penelitian ini adalah alat ini dapat digunakan dengan beberapa jenis permainan dan dapat dikendalikan secara wireless melalui jaringan internet yang dapat dioperasikan pada smarthphone.

The primary objective of the current fire protection system in high-rise buildings is to extinguish fires in close proximity to the detectors. However, in the event of rapidly spreading fires, it is more effective to limit the transmission of fire and smoke. This study aims to develop an IoT-based real-time pre-response system for high-rise building fires that is capable of limiting the spread of fire and smoke. The proposed system collects fire data from sensors and transmits them to a cloud computer for real-time analysis. Based on the analysis results, the cloud computer controls the actions of alarm devices, ventilation equipment, and fine water mist nozzles. The system can dynamically adjust the entire system's behavior in real time by adopting pre-response measures to extinguish fires and limit the spread of fires and smoke. The system was tested on a simulation platform similar to actual high-rise buildings to evaluate its impact on fires and smoke. The results demonstrate the system's effectiveness in extinguishing fires and suppressing the spread of fires and smoke. [ABSTRACT FROM AUTHOR]

Copyright of Przegląd Elektrotechniczny is the property of Przeglad Elektrotechniczny and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The use of smart network applications based on the Internet of Things is increasing, which increases the attractiveness of malicious activities, leading to the need to increase the adequate security of these networks. In this paper, the latest recent breakthroughs in blockchain for the Internet of Things are examined in the context of electronic health (e-health), smart cities, smart transportation, and other applications in this article. Research gaps and possible solutions are discussed, such as security, connection, transparency, privacy, and the IoT's blockchain regulatory challenges. In addition, the most important consensus algorithms used in the blockchain have been discussed, including Proof of Work, Proof of Stake, and Proof of Authority, each of which operates within certain rules. [ABSTRACT FROM AUTHOR]

Physical objects that may communicate with one another are referred to "things" throughout the Internet of Things (IoT) concept. It introduces a variety of services and activities that are both available, trustworthy and essential for human life. The IoT necessitates multifaceted security measures that prioritize communication protected by confidentiality, integrity and authentication services; data inside sensor nodes are encrypted and the network is secured against interruptions and attacks. As a result, the issue of communication security in an IoT network needs to be solved. Even though the IoT network is protected by encryption and authentication, cyber-attacks are still possible. Consequently, it's crucial to have an intrusion detection system (IDS) technology. In this paper, common and potential security threats to the IoT environment are explored. Then, based on evaluating and contrasting recent studies in the field of IoT intrusion detection, a review regarding the IoT IDSs is offered with regard to the methodologies, datasets and machine learning (ML) algorithms. In This study, the strengths and limitations of recent IoT intrusion detection techniques are determined, recent datasets collected from real or simulated IoT environment are explored, high-performing ML methods are discovered, and the gap in recent studies is identified. [ABSTRACT FROM AUTHOR]

Agriculture contributes to large export earnings for many countries and provides food all over the world. However, most agricultural products need some post-harvest processing, such as drying, to extend their shelf life while still maintaining their respective nutrient quality. One popular post-harvest processing method is drying using solar energy. It is a type of renewable energy that is abundant and free. Conventional dryers use grid electricity and can be expensive to operate. Consequently, there is a growing need for cost-effective solar-powered agricultural dryers that is reasonable for smaller-scale farmers. Although current solar dryers are still not on par with modern electricity-powered dryers, solar dryers have lower running costs and are sustainable and able to generate electricity. They can also be used practically anywhere with abundant solar energy. As numerous solar drying technologies have been proposed over the past decade, it is necessary to assess the current state of solar drying technology in the agricultural sector to identify current advancements and potential research gaps. In this paper, a review of existing solar dryers mechanism and the state of the art of solar drying technology research for agricultural products is presented. [ABSTRACT FROM AUTHOR]

Penelitian ini bertujuan untuk melakukan kendali dan monitoring kecepatan dan arah putaran motor induksi tiga fasa berbasis internet of things yang dapat dikendalikan melalui jaringan internet. Pengaturan kecepatan motor dilakukan dengan menggunakan Varibel Speed Drive Sinamic G120 yang dikontrol melalui Programable Logic Controler Simatic S7 1200 1215C. Sistem kontrol dan monitoring motor induksi ini diimplementasikan pada motor induksi 0,75 kW dengan menggunakan multi display, yang terdiri dari Human Machine Interface Simatic KTP 700 Comfort, Personal Computer server dan client berupa Smartphone dan personal computer client. Antara server dengan client dihubungkan melalui internet, sedangkan antara server dengan HMI dan PLC dihubungkan melalui kabel ethernet. Pemograman dilakukan dengan menggunakan TIA portal dan wincc unified PC. Hasil pengujian menunjukan bahwa sistem kontrol dan monitoring kecepatan dan arah putaran motor induksi berbasis internet of things yang diusulkan telah bekerja dengan baik, dimana semua display yang digunakan sebagai interface untuk kontrol dan monitor motor, baik pada server maupun pada client telah sukses menampilkan data motor yang dimonitor dan juga telah sukses mengendalikan motor sesuai dengan yang diinginkan.