Jul 2026· International Journal of Interactive Mobile Technologies (ijim)· 0 citations
TL;DR
Findings indicate that the proposed framework serves as an innovative prototype for Smart Health management within higher education institutions, aligned with the global Smart Campus paradigm.
Abstract
This study aimed to (1) design and develop an IoT-based hardware system for real-time air pollution monitoring, (2) develop an interactive mobile application for reporting and alert notifications, and (3) evaluate the system’s spatial stability and data transmission performance. The proposed framework integrates Internet of Things (IoT) technology with cloud-based database architecture. The sensing node incorporates a SEN55 environmental sensor and an ESP32 microcontroller to collect key parameters, including PM2.5, VOC Index, and NOx Index. Sensor readings are processed using an edge aggregation algorithm to reduce signal noise before being stored in Firebase Realtime Database for real-time synchronization with the “React AQI” mobile application, developed using the React Native framework. The application supports multilingual visualization in Thai, English, and Chinese. Experimental results demonstrated a high average Data Delivery Ratio (DDR) of 94.76%, with data reliability ranging between 95.7% and 97.5%. A 20-day spatial comparative deployment conducted at Building 22 and Building 26 revealed consistent differentiation in pollution levels across locations, with a mean PM2.5 difference of 1.54 µg/m3. The system effectively visualized pollution trends through interactive graphical analytics. These findings indicate that the proposed framework serves as an innovative prototype for Smart Health management within higher education institutions, aligned with the global Smart Campus paradigm.
This paper presents the design, development and evaluation of an Internet of Things (IoT)-based smart waste management system aimed at addressing the inefficiencies and public health concerns associated with traditional waste collection methods. The proposed system integrates ultrasonic sensors for real-time bin fill-level detection, a rain sensor for environmental compensation, an ESP32 microcontroller for data processing and transmission, and a dual-mode feedback mechanism via a local LCD display and a remote web dashboard. Experimental results demonstrate a 99% accuracy in fill-level and rain detection, with data updates to the cloud platform (ThingSpeak) occurring within 2 seconds of a 15-second reporting interval. The system's robustness, low cost, and energy efficiency highlight its potential for scalable deployment in urban environments, contributing to cleaner, smarter communities.
O. Saeed, Ayesha Noroz, Maimoona Waqar et al.· Natural and Applied Sciences...· 0 citations
The design and implementation of an Internet of Things (IoT)-based real-time kitchen monitoring and automation system aimed at enhancing safety, efficiency, and intelligent control within kitchen environments is presented.
Simon Usiju Chagwa, P. B. Zirra· Journal of Analytical and Ap...· 0 citations
To prevent resource waste in traditional agricultural practices and to respond instantly to environmental changes, this study develops a low-cost, multi-parameter smart greenhouse monitoring system based on the Internet of Things (IoT). The system is built on the high-performance STM32F407VGT6 microcontroller, designed for embedded systems, and manages a hybrid sensor network that simultaneously collects temperature, humidity, pressure, air quality, soil moisture, and light intensity data. The unique aspect of this work is that, thanks to the developed C++-based wrapper software architecture, sensors with different communication protocols can be synchronized on a single embedded system, and raw electrical data can be converted into meaningful percentage values for the end user. The obtained data is visualized in real-time locally on an SSD1306 OLED screen and remotely on the Blynk platform via an ESP8266 Wi-Fi module. Test results have shown that the system measures environmental data with high accuracy and transmits it to the cloud server with a response time of less than two seconds. In conclusion, this study offers an economical IoT-enabled smart farming solution for small-scale producers and creates a robust technological infrastructure for future fully autonomous control systems.
Mustafa Gökhan Dağhan, Mohammad Ruhul Amin Bhuiyan, Hayati Mamur· Soma Meslek Yüksekokulu Tekn...· 0 citations
The growing threats to river water quality demand innovative approaches for effective monitoring and protection. This paper proposes an Internet of Things (IoT)-based river water quality monitoring system to address this challenge. The proposed system utilizes a network of sensors strategically deployed within the river, measuring crucial parameters like temperature, pH, dissolved oxygen, turbidity, and conductivity. Sensor data is continuously transmitted wirelessly to a central hub for processing and analysis. Utilizing cloud computing platforms, the system enables real-time data visualization and analysis, allowing for prompt identification of potential pollution events. Additionally, the system integrates alerting mechanisms to notify relevant authorities, facilitating timely interventions. This paper presents the design, implementation, and field testing of the proposed system, along with a thorough evaluation of its performance. The results demonstrate the system's effectiveness in capturing comprehensive water quality data, facilitating real-time monitoring, and enabling proactive water management strategies.
E. Amrutha, Dinesh Ram S P, Ranil Vikram P· International Journal of Lat...· 0 citations
Most Internet of Things (IoT)-based environmental monitoring systems primarily present raw sensor data, requiring users to interpret environmental conditions manually. This research focuses on developing a web-based IoT monitoring system for temperature and humidity, incorporating a Mamdani Fuzzy Logic Inference System (FIS) to interpret environmental conditions more effectively and support informed decision-making. The proposed system's novelty lies in integrating real-time IoT monitoring with fuzzy inference, enabling evaluation based on gradual transitions in temperature and humidity rather than rigid threshold boundaries. The system was implemented using an ESP32 microcontroller, a DHT22 sensor, a MySQL database, and a web-based dashboard. System evaluation included functional testing, end-to-end latency measurement, and continuous monitoring to assess system uptime and transmission performance. The functional testing confirmed that all major system modules operated successfully. The system achieved an average end-to-end latency of 230.02 ms across 50 consecutive transmissions and 100% uptime during an 8-hour continuous monitoring period, with 4,954 recorded transmissions and an average transmission interval of 5.81 s. The results show that the proposed system provides responsive, continuous environmental monitoring while integrating fuzzy-based environmental assessment to support more informed decision-making.
Keywords – Internet of Things, Environmental Monitoring, Web Monitoring, Mamdani Fuzzy Logic, Decision Support
Gaguk Suprianto, Muhammad Septama Prasetya· Techno.Com· 0 citations
Abstract
The Internet of Things (IoT) has emerged as one of the most significant technological advancements in recent years, enabling seamless communication and interaction among physical devices through the Internet. IoT technology has transformed traditional monitoring and control systems by providing real-time data collection, remote accessibility, intelligent decision-making, and automated control mechanisms. The increasing demand for smart environments in sectors such as smart homes, healthcare, agriculture, industrial automation, and smart cities has accelerated the adoption of IoT-based solutions. This dissertation presents the design and implementation of an IoT-based smart system for real-time monitoring and automation using low-cost hardware components, cloud computing platforms, and mobile applications.
The primary objective of this research is to develop an efficient, reliable, and scalable IoT-based monitoring system capable of collecting environmental data, transmitting information to cloud servers, and enabling remote monitoring and automated control. The proposed system integrates NodeMCU ESP8266 as the central processing unit with sensors such as the DHT11 temperature and humidity sensor and the PIR motion sensor. These sensors continuously monitor environmental conditions and transmit the collected data to cloud platforms through wireless communication. ThingSpeak is used as the cloud platform for data storage, visualization, and analysis, while the Blynk mobile application provides users with real-time monitoring and remote control capabilities.
The development process involved hardware configuration, software programming, cloud integration, and system testing. The NodeMCU microcontroller was programmed using Arduino IDE to acquire sensor readings, establish wireless connectivity, and communicate with cloud services. The collected data was uploaded to the cloud platform and displayed through graphical dashboards for real-time observation. Furthermore, automation functionalities were incorporated through relay modules that enable automatic control of connected devices based on predefined threshold values and environmental conditions.
Experimental investigations were conducted to evaluate the performance and effectiveness of the proposed system. The results demonstrated successful real-time monitoring of temperature, humidity, and motion detection parameters. Sensor data was accurately transmitted to the cloud platform and displayed on the mobile application with minimal delay. The automation features successfully triggered control actions whenever predefined conditions were satisfied. The system also demonstrated reliable communication between sensors, cloud servers, and end users, thereby validating the feasibility of the proposed approach.
A comparative analysis between traditional monitoring systems and the proposed IoT-based solution revealed significant improvements in terms of automation, accessibility, data management, operational efficiency, and remote monitoring capabilities. The implementation confirmed that IoT technology can substantially reduce manual intervention, improve response time, and enhance system effectiveness. Despite challenges such as network dependency, security concerns, and sensor limitations, the developed system proved to be a cost-effective and practical solution for intelligent monitoring and automation applications.
Zarreen Fatima, A. Farooqi· International Scientific Jou...· 0 citations
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