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Human activity recognition (HAR) is a technology that infers current user activities by using the available sensory data network. Research on activity recognition is considered extremely important, particularly when it comes to delivering sensitive services such as healthcare services and live tracking assistance and autonomy. For this purpose, many researchers have proposed a knowledge-driven approach or data-driven reasoning for identification techniques. However, there are multiple limitations associated with these approaches and the resulting models are typically not complete enough to capture all types of human activities. Thus, recent works have suggested combining these techniques through a hybrid model. This paper's goal is to give a brief overview of activity recognition implementation approaches by looking at various sensing technologies used to gather data from internet of things (IoT) gadgets, looking at preprocessing and feature extraction approaches, and then comparing methods used to identify human activities in smart homes, and highlighting their strengths and weaknesses across various fields. Numerous pertinent works were located, and their accomplishments were assessed. [ABSTRACT FROM AUTHOR]

Persistent security challenges in Industry 4.0 due to the limited resources of IoT devices necessitate innovative solutions. Addressing this, this study introduces the ASCON algorithm for lightweight authenticated encryption with associated data, enhancing confidentiality, integrity, and authenticity within IoT limitations. By integrating Digital Twins, the framework emphasizes the need for robust security in Industry 4.0, with ASCON ensuring secure data transmission and bolstering system resilience against cyber threats. Practical validation using the MQTT protocol confirms ASCON's efficacy over AES-GCM, highlighting its potential for enhanced security in Industry 4.0. Future research should focus on optimizing ASCON for microprocessors and developing secure remote access tailored to resource-constrained devices, ensuring adaptability in the digital era. [ABSTRACT FROM AUTHOR]

Sleep apnea, characterized by breathing interruptions or slow breathing at night, can cause various health issues. Detecting respiratory rate (RR) using Wireless Fidelity (Wi-Fi) can identify sleep disorders without physical contact avoiding sleep disruption. However, traditional methods using Network Interface Cards (NICs) like the Intel Wi-Fi Link 5300 NIC are often costly and limited in channel state information (CSI) resolution. Our study introduces an effective strategy using the affordable ESP32 single-board computer for tracking RR through detailed analysis of Wi-Fi signal CSI. We developed a technique correlating Wi-Fi signal fluctuations with RR, employing signal processing methods—Hampel Filtering, Gaussian Filtering, Linear Interpolation, and Butterworth Low Pass Filtering—to accurately extract relevant signals. Additionally, noise from external movements is mitigated using a Z-Score for anomaly detection approach. We also implemented a local peak function to count peaks within an interval, scaling it to bpm for RR identification. RR measurements were conducted at different rates—Normal (12–16 bpm), Fast (>16 bpm), and Slow (<12 bpm)—to assess the effectiveness in both normal and sleep apnea conditions. Tested on data from 8 participants with distinct body types and genders, our approach demonstrated accuracy by comparing modeled sleep RR against actual RR measurements from the Vernier Respiration Monitor Belt. Optimal parameter settings yielded an overall average mean absolute deviation (MAD) of 2.60 bpm, providing the best result for normal breathing (MAD = 1.38). Different optimal settings were required for fast (MAD = 1.81) and slow breathing (MAD = 2.98). The results indicate that our method effectively detects RR using a low-cost approach under different parameter settings. [ABSTRACT FROM AUTHOR]

Persistent security challenges in Industry 4.0 due to the limited resources of IoT devices necessitate innovative solutions. Addressing this, this study introduces the ASCON algorithm for lightweight authenticated encryption with associated data, enhancing confidentiality, integrity, and authenticity within IoT limitations. By integrating Digital Twins, the framework emphasizes the need for robust security in Industry 4.0, with ASCON ensuring secure data transmission and bolstering system resilience against cyber threats. Practical validation using the MQTT protocol confirms ASCON’s efficacy over AES-GCM, highlighting its potential for enhanced security in Industry 4.0. Future research should focus on optimizing ASCON for microprocessors and developing secure remote access tailored to resource-constrained devices, ensuring adaptability in the digital era.

This article focuses on researching and constructing a system for controlling and monitoring important parameters related to the poultry egg incubation, such as temperature, humidity, egg turning, light, ventilation, and egg cooling, applying network connectivity technologies and utilizing advanced microcontrollers. The system's functions meet real-time requirements such as: real-time data from the incubation chamber can be controlled and monitored directly or remotely via a personal computer. Through this, users can adjust the parameters on the system to achieve the highest success rate in the incubation process. Experimental results show that the system operates stably with a hatch rate of nearly 95%, meeting the requirements set out by the design research. The actual product is highly robust, easy to install, operate, maintain, and service.

In farming, clashes between humans and animals create significant challenges, risking crop yields, human well-being, and resource depletion. Farmers use traditional methods like electric fences to protect their fields but these can harm essential animals that maintain a balanced ecosystem. To address these fundamental challenges, our research presents a fresh solution harnessing the power of the Internet of Things (IoT) and deep learning. In this paper, we developed a monitoring system that takes advantage of ESP32-CAM and Raspberry Pi in collaboration with optimised YOLOv8 model. Our objective is to detect and classify objects such as animals or humans that roam around the field, providing real-time notification to the farmers by incorporating firebase cloud messaging (FCM). Initially, we have employed ultrasonic sensors that will detect any intruder movement, triggering the camera to capture an image. Further, the captured image is transmitted to a server equipped with an object detection model. Afterwards, the processed image is forwarded to FCM, responsible for managing the image and sending notifications to the farmer through an Android application. Our optimised YOLOv8 model attains an exceptional precision of 97%, recall of 96%, and accuracy of 96%. Once we achieved this optimal outcome, we integrated the model with our IoT infrastructure. This study emphasizes the effectiveness of low-power IoT devices, LoRa devices, and object detection techniques in delivering strong security solutions to the agriculture industry. These technologies hold the potential to significantly decrease crop damage while enhancing safety within the agricultural field and contribute towards wildlife conservation. [ABSTRACT FROM AUTHOR]

The advent of Internet of Things (IoT) technology has paved the way for innovative solutions in various domains, including aquarium maintenance. An IoT-based automated water changing system emerges as a promising solution to ensure a clean and healthy environment for aquarium inhabitants, thereby alleviating basic chores, particularly for aquarium hobbyists. Conventional solutions often fall short in reliability and affordability, merely focusing on water replacement without addressing other crucial factors. In contrast, this novel system integrates cutting-edge features, leveraging wireless monitoring facilitated by Home Assistant and incorporating water seasoning capabilities. Unlike existing systems, which lack comprehensive monitoring, this solution monitors a plethora of water parameters including water height, pH levels, salinity, temperature, and dissolved solids. This holistic approach enables the system to make informed decisions based on real-time data. Utilizing the gathered data, the system employs advanced algorithms to determine requisite actions. For instance, upon detecting a lower water level, it triggers the water vault to replenish water, ensuring optimal water volume for aquatic life. Additionally, it regulates temperature through heating and cooling mechanisms, ensuring the maintenance of ideal conditions for aquatic organisms. Moreover, the system proactively addresses anomalies by generating indicator requests for parameters beyond its operational scope, thereby facilitating timely intervention by the user. By amalgamating state-of-the-art IoT technology with comprehensive water monitoring and proactive decision making capabilities, this automated water changing system represents a significant advancement in aquarium maintenance, promising enhanced efficiency, reliability, and ultimately, a healthier aquatic ecosystem. [ABSTRACT FROM AUTHOR]

Fertigation system has been widely used by farmers to automate some processes of crops productions. A conventional system requires workers to prepare a fertilizer mixture, before transferring it into a main storage tank to be mixed with water. Then, electrical conductivity (EC) of the mixture will be measured. The existing fertigation system still relies heavily on workers and is manually operated and prone to human error. Therefore, internet of things (IoT) based fertigation system has been developed to deliver the fertilizer mixture with consistent EC value automatically to the plants. The main system controller is designed using ESP32 development module. The operation of the system can be monitored using an IoT dashboard and farmers can also control the system remotely. Alert will be given to the farmers if the condition of the system or plant does not meet the predefined settings. The values of EC together with temperature and humidity sensors are recorded for further analysis. A testbed is set up to provide fertigation to 120 polybags eggplants. Using the proposed fertigation system, the eggplants have been harvested earlier, therefore reducing the fertilizer usage. The cost of this IoT based fertigation system is lower compared to existing commercial products. [ABSTRACT FROM AUTHOR]

A low-cost spin coater with a wireless remote system that can deposit thin films of uniform thickness and quality at a significantly lower cost than traditional methods. The system consists of three main parts, a motorized spindle, a spin-coating head, and a control system connected to the network. The mechanical design on the mechanical part, spin coater system design with ESP32, and implementation of wireless control through visual basic. The network-enabled control system allows for real-time monitoring and adjustment of the deposition process, which can improve efficiency and reproducibility. This low-cost spin coating system represents a promising solution for organizations seeking to access thin film deposition technology at a fraction of the cost of traditional systems. By integrating wireless IoT control into low-cost spin coaters, the impact of this technology on coating uniformity will provide valuable insights for future advancements in this field. [ABSTRACT FROM AUTHOR]

The library is a source of knowledge, information, and support for learning. It is equipped with facilities to support comfort and maintain concentration while carrying out activities in the library. For human resources to progress further, libraries must be made as comfortable as possible to support learning. This study aims to design a noise and CO2 control device in an IOT (Internet of Things) based library by using 4 sound sensors KY-037 to detect noise and 1 MQ-135 sensor to detect CO2 gas. This research method uses a literature review study. The noise and CO2 control device in the IOT (Internet Of Things) based library has been completed and can work as planned, the accuracy obtained from the KY-037 sound sensor is quite high, which is 97.6%. However, the good thing is that if the sensor accuracy is improved again, the accuracy obtained from the MQ-135 sound sensor is also quite high, which is 99.16%. Conclusion If the accuracy of the sensor is improved again, the web server runs smoothly using AJAX (Asynchronous et al.) so that the resulting website does not need to load the entire page and the ESP32 as a microcontroller can control the entire system well. [ABSTRACT FROM AUTHOR]

Backpacks are the main choice for students as a means of carrying school supplies and materials, but often they do not pay attention to the weight of the load they carry every day, potentially causing injuries and pain in the back. This study aims to design and implement a capacity limit measuring device on children's school bags using the ESP32 microcontroller as the control center. The tool is equipped with a 10kg load cell sensor to accurately measure the weight of the bag, as well as a keypad as a user interface to easily enter the child's weight. Safety is also considered with the addition of a buzzer as an alarm if the weight of the bag's capacity exceeds the set limit. GPS trackers are also integrated to monitor the geographical location of bags, allowing parents to monitor the movement of children and the location of bags directly through Telegram bots. With ESP32 as the brain, this tool provides a comprehensive solution to maintain the health and safety of children in carrying their school load. This tool also utilizes Telegram technology to provide direct notifications about the weight and location of children's bags to parents or other users. Telegram bots connected to this tool automatically transmit this information, providing additional convenience and security for users. [ABSTRACT FROM AUTHOR]

In this research, the system is designed to monitor parameters of residential solar power sources such as voltage, current, power capacity, power factor and energy consumption. These parameters are measured by a highly accurate PZEM circuit and the specifications are suitable for residential solar power sources. Measurement results will be sent to the main control circuit (ARM controller) via the UART communication standard to analyze and filter the necessary data. The data of that parameter will then be displayed at the system installation site using the TFT screen. After an installation period, the control circuit will send measurement parameters to the dedicated WiFi module (ESP32), the WiFi module will continue to send parameters to the cloud server for storage and monitoring. The system also builds applications that run on many operating systems, can access data, and display data in real time using IoT technology. It should be noted that the system can still operate in the event of loss or absence of WiFi signal by using Bluetooth signal. In addition, the designed system also has the function of remotely controlling on/off the solar power supply to the loads when an incident occurs, ensuring safety for the electrical system. [ABSTRACT FROM AUTHOR]

Technological advancements are propelling medical technology towards automation through the application and widespread use of automatic control, sensing, and Internet of Things (IoT) technologies. Currently, IoT technology has been extensively applied in medical devices, aiming to ensure patient safety through more real-time detection and more effective management. In the monitoring of intravenous infusion, accurately sensing the infusion conditions in real time is particularly important. This article introduces a low-cost smart infusion device based on IoT technology, which controls the infusion rate with a peristaltic pump and monitors the volume of fluid delivered. It uses an improved, self-calibrating weighing sensor to achieve the real-time closed-loop control of the flow rate, ensuring patient safety. Additionally, the Blynk dashboard can be used for monitoring and controlling the flow rate and infusion volume. [ABSTRACT FROM AUTHOR]

Aquaculture provided 43% of the aquatic animal food consumed by humans in 2007, and it is anticipated to expand even more to meet the increasing future demand. Marine Science Techno Park (MSTP) is one of the Techno Parks in Indonesia and is located in Teluk Awur, Jepara. MSTP has an intensive system of Vannamei shrimp farming activities. The challenge that has been faced annually is the organic matter of the remaining shrimp feed that accumulates in the waters can cause a decrease in pond water quality. Ammonia-N anions derived from the decomposition of feed residues can cause toxins in shrimp culture ponds which can further interfere with shrimp survival. The objective of this study is to design a self-controlled water quality monitoring system that is equipped with an early warning system based on internet of things (IoT) and to implement the design for analyzing the water quality including dissolved oxygen (DO), pH, and temperature in the Vannamei farming pond of MSTP UNDIP through integrating IoT which is equipped with an early warning system. If the water quality reaches a threshold value, the monitoring system will send a sound signal to the buzzer followed by sending an alert notification in real-time conditions automatically to a smartphone. [ABSTRACT FROM AUTHOR]

Modern agriculture makes use of a variety of poly house systems. Poly house systems can be used to grow healthier crops in larger quantities. Temperature, humidity, and wetness are examples of environmental variables that influence plant growth. This strategy protects crops from insects, uncertain weather, and sickness. The poly house will address all deficits for hazardous seasonable crops as well as electricity consumption by harnessing solar energy. The factors that influence the development of crops are monitored using appropriate sensors. The ESP 32 microprocessor will control the optimal conditions in the poly house system. [ABSTRACT FROM AUTHOR]

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Di era Internet of Things (IoT) yang semakin berkembang, Wireless Sensor Network (WSN) berperan penting dalam menghubungkan perangkat, memfasilitasi pertukaran data, dan menghemat sumber daya. Namun, WSN masih menghadapi tantangan operasional, seperti pengumpulan data sensor yang luas, operasional dengan energi terbatas, dan adaptasi dengan dinamika lingkungan yang berubah. Penelitian ini mengkaji implementasi protokol Ad hoc On-Demand Distance Vector (AODV) bersama ESP-NOW pada mikrokontroler ESP32, dengan tujuan utama meningkatkan efisiensi operasional WSN. Metode pengujian yang digunakan melibatkan pengujian dalam berbagai kondisi WSN, baik untuk node statis maupun dinamis, di lingkungan dengan dan tanpa hambatan fisik, untuk mengevaluasi kinerja AODV secara menyeluruh. Hasil pengujian menunjukkan tingkat keberhasilan komunikasi antar-node sebesar 86,6%, menandakan potensi signifikan dari integrasi ESP32 dan ESP-NOW dalam implementasi AODV di WSN. Penelitian ini penting karena membantu dalam mengatasi tantangan operasional dalam Wireless Sensor Network (WSN) yang merupakan bagian integral dari IoT, dan kontribusinya terletak pada pengembangan dan implementasi protokol AODV dengan ESP-NOW pada ESP32, yang berpotensi meningkatkan efisiensi dan adaptabilitas WSN, sehingga mendukung perkembangan dan peningkatan aplikasi IoT di masa depan. Abstract In the rapidly evolving era of the Internet of Things (IoT), Wireless Sensor Networks (WSN) play a crucial role in connecting devices, facilitating data exchange, and conserving resources. However, WSNs continue to face operational challenges, such as extensive sensor data collection, limited energy operation, and adaptation to changing environmental dynamics. This study examines the implementation of the Ad hoc On-Demand Distance Vector (AODV) protocol in conjunction with ESP-NOW on the ESP32 microcontroller, primarily aiming to enhance the operational efficiency of WSNs. The testing methodology employed involves trials under various WSN conditions, for both static and dynamic nodes, in environments with and without physical obstacles, to comprehensively evaluate the performance of AODV. The results show a successful inter-node communication rate of 86.6%, indicating the significant potential of integrating ESP32 and ESP-NOW in the AODV implementation within WSNs. This research is important as it helps in addressing the operational challenges in Wireless Sensor Networks (WSN), which are an integral part of IoT, and its contribution lies in the development and implementation of the AODV protocol with ESP-NOW on ESP32, which has the potential to enhance the efficiency and adaptability of WSNs, thereby supporting the development and improvement of IoT applications in the future.

Sistem Gerbang otomatis, atau autogate, digunakan untuk memudahkan proses pembukaan dan penutupan Gerbang. Namun, dalam penggunaannya, muncul beberapa tantangan. Salah satunya adalah keterbatasan jarak akses pada sistem kendali autogate yang hanya menggunakan remote RF. Selain itu, sistem keamanan saat Gerbang menutup masih memiliki kelemahan, yaitu risiko potensial Gerbang menabrak objek yang berada di jalurnya. Untuk mengatasi tantangan-tantangan tersebut, penelitian ini bertujuan untuk merancang sistem pengendali Gerbang geser otomatis yang mengadopsi PLC sebagai pengontrol utama. Sistem ini juga akan menambahkan akses kontrol melalui smartphone berbasiskan android yang terhubung ke jaringan internet dengan bantuan modul ESP32 serta menggunakan basis data dari Firebase. Selain itu, sensor photobeam akan dimasukkan sebagai elemen pendeteksi objek yang berada di lintasan Gerbang sebagai system pengamannya. Dari Hasil implementasi dan analisis yang telah dilakukan, alat ini berhasil beroperasi sesuai dengan desainnya. Penggunaan smartphone sebagai kendali mampu mengatasi keterbatasan jarak akses, dengan waktu respons sekitar 0,5 hingga 3 detik, bergantung pada kualitas jaringan internet. Sensor photobeam juga berhasil mendeteksi objek yang berada di lintasan Gerbang, sehingga sistem kendali dapat menghentikan dan membuka Gerbang secara otomatis ketika objek terdeteksi saat Gerbang sedang menutup.

This research focuses on a comprehensive analysis of the energy efficiency of the Renesas DA16200 microcontroller. The investigation adopts a comparative approach, directly contrasting the power consumption of the DA16200 with the widely used ESP8266 controller under identical operating conditions. The primary metric employed to assess energy efficiency is average battery life. Additionally, a detailed examination of current consumption is conducted across various operational modes, encompassing active states like data exchange, reception, and transmission, as well as low-power sleep mode. This analysis extends beyond simply measuring peak current draw. Transient current profiles are captured, providing time-resolved insights into how current consumption fluctuates throughout different operational phases. This granular data enables a deeper understanding of the microcontrollers' energy utilization patterns. Furthermore, the research explores and evaluates techniques for minimizing energy consumption specifically in the ESP8266. These findings are then juxtaposed against the inherent energy-saving features of the DA16200 microcontroller. To facilitate a precise and verifiable comparison, a custom test bench accommodating both the DA16200 and ESP8266 is designed and implemented. This controlled environment ensures consistency in operating conditions and minimizes external variables that could influence the results. The culmination of this research is the presentation of a comprehensive analysis, detailing the comparative energy consumption profiles of the studied microcontrollers. This data forms the foundation for objectively evaluating their suitability for various low-power the Internet of Things applications.

Solar electric vehicle charging can substantially reduce carbon emissions compared to conventional utility grid-based electric vehicle charging. In the future, the need for the use of electric vehicle charging will continue to increase so that an energy charging management system that is simple and has ubiquitous components is needed. This paper presented a simple charging management system. The current solution is full of complexity with various algorithms, deep learning and machine learning solutions, and artificial intelligence, which can lead to errors for which no known solution exists. The main novelty in the proposed strategy is to compare the components used to get a simple but reliable system. The component that will compare is Raspberry Pi and ESP32. The ESP32 can offset the advantages of the Raspberry Pi with the help of Blynk, so for a simple and cheaper but reliable system, the ESP32 system is better for an energy charging management system.

Indonesia is one of the countries that has the richest biodiversity in the world such as the diversity of fish species, so many people use them to keep at home as ornamental fish. However, keeping fish with various activities outside the house can result in uncontrolled fish feeding, when excessive feed is given it can affect the environment of the aquarium where the fish are kept, namely the pH value of the water. Based on this, a tool was created that can monitor the pH of aquarium water which is equipped with a control system. Taking advantage of technological advances in this era, monitoring can be done on smartphones via the WhatsApp application. The microcontroller used ESP 32, is equipped with a Wifi module for internet access, so that it can store cloud-based water pH value reading data on the twilio web. Control will be carried out with the aim of maintaining the pH value of the water in the aquarium, namely if the reading results of the pH value are not at a value of 6-8. When the pH value is too low, a liquid that can increase the pH value will be pumped into the aquarium. The same thing will be done when the pH value is high, liquid to lower the pH value will be pumped into the aquarium.

Water is the most essential element for human life after air, hence the amount and quality of water resources must be monitored by the appropriate government agencies. The goal of this research is to create and implement an IoT‐based rivers monitoring prototype system. Two basic components make up the proposed system: the first component represents the node points, and the second component represents the control point. In order to achieve continuous updates of the information via Internet from the node side, ESP32 with its built‐in Wi‐Fi adapter was utilized. The node should pinpoint three major situations, Normal, High. and Low of river water, and then transfer it using IoT to the control point to take an action depending on conditions at the river. © 2023 Institute of Electrical Engineer of Japan and Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

The field of smart agriculture is ranked among the top areas that uses the internet of things (IoT), whose goal is to increase the quantity and quality of agricultural productivity. The aim of this work is to realize a new device that will be cost-effective, reliable, and autonomous using a solar panel to provide electricity in large-scale agricultural fields, ESP32 to interconnect IoT sensors and the long range (LoRa) data transmission protocol to guarantee connectivity in places where there is no internet, whose objective is to monitor and irrigate agricultural fields only when there is a need for water. The data received by the sensors is sent to mobile app users via the Blynk cloud. The performance of our new approach is measured in terms of energy savings. This new model of irrigation and smart monitoring will improve the efficiency of farming techniques. [ABSTRACT FROM AUTHOR]

In the present day, IoT technology is widely applied in the field of medical devices to facilitate real-time monitoring and management by medical staff, thereby better-ensuring patient safety. In IoT intravenous infusion monitoring sensors, it is particularly important to ensure that air bubbles are not infused into the patient's body. The most common method for bubble detection during intravenous infusions is the use of infrared or laser sensors, which can usually meet design requirements at a relatively low cost. Another method is the use of ultrasonic detection of bubbles, which achieves high accuracy but has not been widely promoted in the market due to higher costs. This proposed work introduces a new type of sensor that detects bubbles by monitoring changes in capacitance between two electrodes installed at the surface of the infusion pipe. If this sensor is deployed on the ESP32 platform, which is widely used in embedded IoT devices, it can achieve 35 μL bubble detection precision with an average power consumption of 5.18 mW and a mass production cost of $0.022. Although the precision of this sensor is significantly lower than the low-cost IR bubble sensor, it still satisfies the design requirement of the IV infusion IoT sensor. [ABSTRACT FROM AUTHOR]

Natural activities such as mountain climbing are activities that require a good communication system, whether it is for the purposes of knowing the position or communication to fellow climbers in a small or large group. Cases of missing climbers often occur in the mountains, so communication in search in mountainous areas becomes one of the difficult things when searching. The purpose of designing LoRa RFM95 repeaters with a frequency of 915 MHz based on ESP32 is to improve the range and stability of communication in LoRa networks. International scale research on LoRa performance testing implies that the LoRa coverage distance is strongly influenced by the conditions of the tested area. Therefore, a repeater is needed for LoRa RFM95 to increase the range distance which refers to the System Development Life Cycle (SDLC) method. The results of tests conducted for transmitters and receivers can communicate as far as 80 meters with line of sight (LoS) conditions and 60meters with non-line of sight (NLOS) conditions. The results of trials conducted by repeaters can extend communication range as far as 60 meters with line of sight conditions and 40 meters with non-line of sight (NLOS) conditions. [ABSTRACT FROM AUTHOR]

In recent years, inexpensive and easy to use robotics platforms have been incorporated into middle school, high school, and college educational curricula and competitions all over the world. Students have access to advanced microprocessors and sensor systems that engage, educate, and encourage their creativity. In this study, the capabilities of the widely available VEX Robotics System are extended using the wireless ESP-NOW protocol to allow for real-time data logging and to extend the computational capabilities of the system. Specifically, this study presents an open source system that interfaces a VEX V5 microprocessor, an OpenMV camera, and a computer. Images from OpenMV are sent to a computer where object detection algorithms can be run and instructions sent to the VEX V5 microprocessor while system data and sensor readings are sent from the VEX V5 microprocessor to the computer. System performance was evaluated as a function of distance between transmitter and receiver, data packet round trip timing, and object detection using YoloV8. Three sample applications are detailed including the evaluation of a visionbased object sorting machine, a drivetrain trajectory analysis, and a proportionalintegral-derivative (PID) control algorithm tuning experiment. It was concluded that the system is well suited for real time object detection tasks and could play an important role in improving robotics education. [ABSTRACT FROM AUTHOR]

This paper highlights the need to address fire monitoring in densely populated urban areas using innovative technology, in particular, the internet of things (IoT). The proposed methodology combines data collection through sensors with instant notifications via text messages and images through the user's email. This strategy allows a fast and efficient response, with message delivery times varying from 1 to 4 seconds on Internet connections. It was observed that the time to send notifications on 3G networks is three times longer compared to Wi-Fi networks, and in some 3G tests, the connection was interrupted. Therefore, the use of Wi-Fi is recommended to avoid significant delays and possible bandwidth issues. The implementation of fuzzy logic in the ESP32 microcontroller facilitates the identification of critical parameters to classify notifications of possible fires and the sending of evidence through images via email. This approach successfully validated the results of the algorithm by providing end users with detailed emails containing information on temperature, humidity, gas presence and a corresponding image as evidence. Taken together, these findings support the effectiveness and potential of this innovative solution for fire monitoring and prevention in densely populated urban areas. [ABSTRACT FROM AUTHOR]

Ikan merupakan sumber makanan yang mudah diperoleh di indonesia, ikan tidak hanya dapat ditemukan di sungai dan di laut saja. Seiring dengan perkembangan teknologi ikan dapat dibudidayakan di rumah dengan lahan yang terbatas. Dalam budidaya ikan, kualitas air memiliki pengaruh besar terhadap produksi ikan. Terdapat beberapa parameter yang dapat dijadikan acuan bahwa air dikatakan memiliki kualitas yang baik yaitu suhu air, pH air, dan kekeruhan pada air. Pada penelitian ini menggunakan ESP32 sebagai mikrokontroler untuk memproses pembacaan sensor suhu DS18B20, sensor pH, dan sensor TDS pada akuarium, dengan data yang dapat dimonitoring melalui LCD dan smartphone. Pada alat ini dapat mengatur ON/OFF pompa berdasarkan parameter kondisi air yang telah ditentukan. Hasil perbandingan antara akuarium yang menggunakan smart akuarium dan akuarium yang tidak menggunakan smart akuarium menunjukkan bahwa menggunakan smart akuarium lebih efektif dalam menjaga kualitas air (pH 6.8, suhu 29.4ºC, kekeruhan 96 ppm) sedangkan tidak menggunakan smart akuarium (pH 3.5, suhu 28.9ºC, kekeruhan 178 ppm). Penggunaan smart akuarium juga lebih efisien karena hanya mengonsumsi rata-rata 64.6 watt per hari dengan biaya bulanan Rp 2.798, dibandingkan dengan pompa kontinyu yang mengonsumsi 324 watt per hari dengan biaya bulanan Rp 14.035. sehingga pompa yang dikendalikan oleh smart akuarium dapat lebih baik dalam menjaga kualitas air dan menghemat pengeluaran biaya penggunaan listrik.