Internet Of Things Connectivity Research Articles

Automated Monitoring System for Rainwater Harvesting Tank at Telkom University

The use of ground tank constructed by Telkom University for Rainwater Harvesting (RWH), is limited to environmental maintenance due to concerns regarding the quality of water in the underground tank. Therefore, this research aims to develop a remote monitoring device that uses Internet of Things (IoT) technology to monitor the pH, water surface, submerged materials, and water clarity levels in ground tank. To achieve the requirements, pH, ultrasonic-based volume, Total Dissolved Solids (TDS), and Turbidity sensors were selected due to the IoT connectivity. The enabling device, namely the ESP 32 microcontroller and Blynk platform were installed on monitoring dashboard on a tablet computer with 4GB of RAM. The result showed that calibration of each sensor had good accuracy, except for the Turbidity sensor due unavailable materials. In conclusion, the RWH monitoring system is suitable for use.

The role of telecommunications in enabling Internet of Things (IoT) connectivity and applications

This review paper explores the pivotal role of telecommunications in enabling Internet of Things (IoT) connectivity and applications, providing a comprehensive overview of the current landscape and future prospects. The primary objective is to synthesize existing research and industry insights to highlight how advancements in telecommunications infrastructure and technology have catalyzed the adoption and expansion of IoT. The review systematically examines the evolution of telecommunications technologies, including 4G, 5G, and emerging network protocols such as Narrowband IoT (NB-IoT) and Long-Term Evolution for Machines (LTE-M). It assesses how these technologies enhance IoT connectivity by providing the necessary bandwidth, low latency, and reliability for real-time data exchange and device interoperability. Key findings from the literature reveal that the deployment of 5G networks has been a game-changer for IoT, offering unprecedented speeds and connectivity capabilities that support a wide range of applications in smart cities, healthcare, agriculture, and industrial automation. Additionally, the paper discusses the role of telecommunications in addressing challenges related to security, scalability, and energy efficiency in IoT deployments. The review concludes that telecommunications are integral to the growth and sustainability of IoT ecosystems. As telecommunications technology continues to advance, its ability to support increasingly complex and ubiquitous IoT applications will drive innovation and enhance efficiency across various sectors. The paper emphasizes the necessity for ongoing investment in telecommunications infrastructure and research to fully exploit the transformative potential of IoT connectivity and applications.

DESIGN AND FABRICATION OF SMART ENVIRO GUARDIAN

This project tackles the challenge of maintaining a comfortable and healthy indoor environment in the face of unpredictable weather conditions. The primary objective is to develop an automated weather monitoring system integrated with a humidifier, leveraging Internet of Things (IoT) technology and a suite of sensors including the DHT11 for temperature and humidity, a rain sensor, an LDR sensor, and a BMP180 barometric pressure sensor. The system aims to monitor real-time weather data and adjust indoor conditions accordingly, enhancing comfort and reducing health risks such as respiratory issues, allergies, and mold growth. Additionally, it provides remote monitoring and real-time alerts through IoT connectivity, improving user convenience and energy efficiency. The methodology includes detailed requirement analysis, hardware and software development, testing, and deployment. This project promises to significantly improve indoor environmental quality, especially in regions with erratic weather patterns, by providing a robust, adaptable solution. Keywords: Automated Weather Monitoring, Climate Control, IoT Technology, Humidifier, DHT11 Sensor, Rain Sensor, LDR Sensor, Energy Efficiency

Enhancing IoT connectivity through spectrum sharing in 5G networks

The integration of the Internet of Things (IoT) into high-performance devices and monitoring systems, spanning domains such as smart building, e-health care, and smart agriculture, necessitates a critical emphasis on advancing mobile communications through efficient spectrum utilization. This research addresses pivotal challenges within agricultural IoT applications, specifically focusing on the substantial decline in spectrum efficiency observed with the increasing escalation of network bandwidth. Acknowledging the absence of comprehensive reviews on 5G resource allocation strategies in the existing literature, our study aims to contribute to a nuanced understanding of their implications for service quality. The identified research gaps underscore an urgent need for heightened efforts to optimize resource allocation in 5G networks. This investigation delves into the intricacies of spectrum sharing and real-time analysis techniques within the 5G and beyond network, with a targeted focus on augmenting agricultural IoT services. Three distinct models, namely (i) Non-Priority Algorithm (NPA), (ii) Reserved Channel Algorithm (RCA) - No Permanent Channels, and (iii) Reserved Channel Algorithm (RCA) - Permanent Channels, were meticulously designed and simulated for Agricultural IoT application scenarios. The methodology encompasses the comprehensive evaluation of performance metrics, including call blocking, termination, and handover, to strategically identify and allocate spectrum resources effectively. The research endeavors to address ongoing challenges pertaining to effective communication, standardization, and data management for diverse 5G IoT devices. In light of these persisting concerns, the study not only seeks to enhance the overall efficiency of 5G IoT networks but also proposes innovative perspectives on intelligent and ingenious spectrum allocation techniques. The anticipated outcomes pledge to optimize the utilization of limited spectrum through novel spectrum-sharing strategies, thereby contributing to the advancement of 5G networks and bolstering agricultural IoT devices and services.

A Survey on Crop Management in Smart Agriculture

The agricultural sector's importance is highlighted by the upcoming global population growth predicted by the food and agriculture organization. This growth will lead to increased food demand. However, traditional farming methods require a lot of time and effort and result in diminishing returns. Recent technological advancements, especially in the Internet of Things (IoT), are changing this landscape by introducing smart agriculture. Smart agriculture aims to improve decision-making and crop management using IoT's connectivity and data analysis capabilities. Artificial intelligence (AI) is becoming crucial in this context, offering speed, accuracy, and cost-effectiveness. Machine learning, a type of AI, is beneficial in detecting yields and forecasting weather. This survey highlights the evolving field of intelligent agriculture, covering topics like crop monitoring, and anomaly detection, and explains the main challenges in farming practices.

IoT - Toxic Gas Detection System in Sewage

The application of IoT and machine learning in gas detection systems for sewage offers an innovative approach to real-time gas detection and enhances environmental safety in industrial and urban environments. This system uses advanced technologies such as the Internet of Things (IoT), machine learning algorithms, and high-performance sensors like the MQ135 and the DHT11 to achieve the best results in the gas concentration measurement and collection. It identifies abnormalities and determines which emission control measures are most effective for specific release points and similar situations. The design of the device includes sensor nodes that are primarily responsible for data collection and a central microcontroller (MCU) that operates a machine learning algorithm for efficient anomaly detection and predictive maintenance. The system uses the IoT connection to regularly send data to cloud platform (Blynk), enabling real time monitoring of gas levels and environmental conditions. The system generates a visual image of the captured data that can be accessed online. Distinctive attributes like accurate gas detection, continuous monitoring, predictive maintenance, remote assessment, and comprehensive data visualization, all contribute to smart decision-making for environmental safety.

An IoT-Based Smart Street Lighting System to Lower Energy Consumption

Smart Lighting System is an automated and intelligent lighting control system that can be deployed across multiple locations or in one location, utilizing various IoT connection protocols, devices, and sensors. The system is able to intelligently adjust to changes in ambient light conditions, traffic patterns, and pedestrian activity through the integration of Internet of Things (IoT) technologies. IoT-enabled sensors are installed in every street light, creating a network that connects to a central control unit. Using real-time data, this system dynamically modifies street light brightness to maximize energy efficiency and improve safety. It provides a simulation and optimization tool for street light placement, considering factors such as street length, light distance, and the number of lights ahead. This tool aids in visualizing the power consumption implications of different configurations, promoting efficient urban planning. Demonstrates the energy-saving potential of the proposed system. As the street light intervals and the number of lights ahead decreases, the optimal street light power significantly reduces, leading to substantial energy savings. The system's ability to dim or turn off lights during low-traffic or well-lit periods contributes to reduced operational costs and enhanced sustainability.

An Eco-Friendly and Low Cost IoT based Room Temperature Control by Fan Speed Regulation for Tropical Use

This work presents an Internet of Things (IoT) based room temperature monitoring and control system by fan speed regulation developed for use in rooms of tropical regions of West Africa. In this work, cutting-edge technologies were integrated, including IoT, and cloud- based monitoring to create a system capable of dynamically remote controlling fan speed based on real- time temperature data. The Dallas DS18B20 Waterproof Temperature Sensor serves as the cornerstone for accurate temperature monitoring. A Microcontroller (Node MCU ESP8266) with Wi-Fi Module facilitates IoT connectivity, allowing users to remotely monitor and control the system through the Blynk Cloud and the Blynk App. A 12V DC table fan, driven by a MOSFET which is being controlled through Pulse Width Modulation (PWM) by the microcontroller, enables fine- tuned speed adjustments. A 16x2 LCD display provides real-time feedback on current temperature and fan speed percentage, enhancing user awareness. The microcontroller programming involves the implementation of an adaptive algorithm for dynamic fan speed control based on the room temperature, user settings and some preset parameters conditioned for tropical region of West Africa. By dynamically adjusting fan speed based on real-time temperature data, the system optimizes energy consumption, providing sustainable and eco-friendly solutions. The circuit was designed and simulated in Proteus software, the code was written in Arduino IDE, tested on breadboard, implemented finally on Veroboard and all fitted inside a suitable box. After testing the system, it worked as expected and it was observed that the fan speed increases as the room temperature increases and vice versa. Also, the fan speed depends both on the room temperature and the set threshold value. It was also observed that the speed of the fan is at its maximum when the temperature is above 40°C. Thus, the developed system is good for room temperature control in the tropical region of West Africa.

Empowering IoT connectivity: unveiling the potential of IoT.Js for enhanced interconnectivity

ABSTRACT The concept of a global Internet of Things (IoT), as proposed by Bart, revolutionizes connectivity by assigning unique digital identities to everyday objects, thereby enabling the development of smarter devices. However, the advancement and expansion of the IoT face significant obstacles and constraints, including energy efficiency and memory usage, which require further investigation. To address these challenges, this study presents a novel framework named IoT.js. This framework aims to facilitate the interconnection of lightweight devices within the web-based IoT ecosystem. These devices, ranging from microcontrollers to those with limited memory capacities, stand to benefit from IoT.js’s utilization of JavaScript for IoT application development. By promoting collaboration among lightweight devices with small memory sizes, IoT.js offers a promising solution to the resource constraints encountered in IoT deployments. This study contributes to the advancement of the IoT landscape by introducing a new approach that not only enables the efficient use of limited resources but also facilitates the seamless interconnection of lightweight devices within the IoT network. Additionally, the study conducts performance analysis to measure the efficacy of the proposed framework. Through rigorous evaluation of key metrics, such as energy efficiency and memory usage, the research findings validate the effectiveness of IoT.js in addressing the challenges associated with IoT deployment. Overall, the proposed IoT.js based approach represents a significant step forward in enhancing interconnectivity within the IoT ecosystem, thereby unlocking new possibilities for the development of innovative IoT applications and services.

Spatial digital twin framework for overheight vehicle warning and re-routing system

Overhead road obstacles present a significant logistical hazard to the heavy vehicle industry. Traditional overheight vehicle warning systems such as passive warning systems (PWS) and active warning systems (AWS) have not adequately reduced the frequency and impact of overheight incidents, encouraging transportation agencies to employ intelligent transport system (ITS) strategies using state-of-the-art advanced technologies. This research takes an innovative approach in developing an immersive user-focused experience, harnessing multi-disciplinary methods and tools to engineer a spatial digital twin prototype for a novel Internet-of-Things (IoT)-based active warning alert and re-routing system (AWARS). LiDAR and 3D GIS were used to model the complex road environment, tailored to the strict fiscal objectives sought by economically mindful organisations. Tree crowns were extracted from near-Infrared aerial imagery and digital elevation models, supplying the dimensions necessary for 3D tree modelling. IoT connectivity was configured using a real-time analytics approach to deliver alerts and re-routing options. The World Traffic Service with live and predictive traffic data was used for the routing application programming interface (API). A standard-configuration common rigid truck (CRT) was inserted into the 3D road environment model to simulate overheight collisions and to ascertain the effect of re-routing on estimated time of arrival (ETA). Longer ETA durations were observed for routes computed by the digital twin. Theoretically, enhanced situational awareness and subsequent reduction of risk likelihood suggests an optimised response to industry demands, despite extended travel times, cultivating a favorable impact on the supply chain through enhanced safety management.

Review on IoT-Driven Infusion Monitoring & Management System

Effective intravenous (IV) infusion management and monitoring are essential in today's healthcare environment to guarantee patient safety and improve the standard of care. In order to overcome the drawbacks of conventional IV drip monitoring techniques, this study describes the creation of a contactless, Internet of Things-driven infusion monitoring and management system. With the use of cutting-edge sensor technology and Internet of Things connection, the suggested system combines real-time IV drip liquid level monitoring and control, delivering precise and ongoing updates. Healthcare practitioners may now monitor and analyse patient data remotely thanks to the gathered data's constant updating and transmission to the Think Speak cloud platform. With its combination of real- time data collecting, cloud-based analytics, and emergency alert features, the proposed contactless IoT-driven infusion monitoring and management system represents a substantial improvement in healthcare technology. Using the power of IoT and cloud computing, this invention seeks to enhance overall patient outcomes, optimize IV treatment administration, and decrease human monitoring efforts. To increase patient safety, the system has an emergency alarm mechanism based on GSM modules. This feature ensures that caregivers are notified promptly of any irregularities or critical IV drip levels, allowing for prompt treatment. By providing real-time signals, the device lessens the risks related to delayed reactions to IV fluid failure or depletion. Formulating a real-time model for IV drip liquid level monitoring is the main goal of the system. By employing non-invasive sensors to identify and record the drip rate and fluid levels, this gadget assures precise tracking without having physical contact with the IV apparatus. Keywords: Internet of Things, ESP32 microcontroller, Biomedical, GSM, Relay, LCD Display.

Analysis of IoT technologies suitable for remote areas in Colombia: Conceptual design of an IoT system for monitoring and managing distributed energy systems

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.

Impact of Optical-to-Electrical Conversion on the Design of an End-to-End Learning RGB-LED-Based Visible Light Communication System

Visible Light Communication (VLC) is emerging as a promising technology to meet the demands of fifth-generation (5G) networks and the Internet of Things (IoT). This study introduces a novel RGB-LED-based VLC system design that leverages autoencoders, addressing the often overlooked impact of optical-to-electrical (O/E) conversion efficiency. Unlike traditional methods, our autoencoder-based system not only improves communication performance but also mitigates the negative effects of O/E conversion. Through comprehensive simulations, we show that the proposed autoencoder structure enhances system robustness, achieving superior performance compared to traditional VLC systems. By quantitatively assessing the impact of O/E conversion—a critical aspect previously overlooked in the literature—our work bridges a crucial gap in VLC research. This contribution not only advances the understanding of VLC systems but also provides a strong foundation for future enhancements in 5G and IoT connectivity.

Synergy of 6G technology and IoT networks for transformative applications

SummaryThe rapid growth of Wi‐Fi networking and intelligent systems, fueled by the emergence of the Internet of Things (IoT), has enabled significant transformative advancements. The imminent arrival of sixth‐generation (6G) wireless networks offers more opportunities as fifth‐generation (5G) wireless networks improve IoT connections. This study explores the potential advantages of 6G technology and IoT networks, focusing on edge intelligence, reconfigurable smart surfaces, Terahertz communications, and blockchain integration. The study examines potential implementation challenges and highlights the potential impact of 6G on IoT device usage. This research outlines potential applications of 6G in many sectors like the internet of vehicles, healthcare, autonomous driving, unmanned aerial vehicles, satellite television, and industrial IoT. This research elaborates on specific research topics related to 6G‐IoT technologies to enhance understanding and practical applicability.

Design and Evaluation of a Low-Power Wide-Area Network (LPWAN)-Based Emergency Response System for Individuals with Special Needs in Smart Buildings.

The Internet of Things (IoT) is a growing network of interconnected devices used in transportation, finance, public services, healthcare, smart cities, surveillance, and agriculture. IoT devices are increasingly integrated into mobile assets like trains, cars, and airplanes. Among the IoT components, wearable sensors are expected to reach three billion by 2050, becoming more common in smart environments like buildings, campuses, and healthcare facilities. A notable IoT application is the smart campus for educational purposes. Timely notifications are essential in critical scenarios. IoT devices gather and relay important information in real time to individuals with special needs via mobile applications and connected devices, aiding health-monitoring and decision-making. Ensuring IoT connectivity with end users requires long-range communication, low power consumption, and cost-effectiveness. The LPWAN is a promising technology for meeting these needs, offering a low cost, long range, and minimal power use. Despite their potential, mobile IoT and LPWANs in healthcare, especially for emergency response systems, have not received adequate research attention. Our study evaluated an LPWAN-based emergency response system for visually impaired individuals on the Hazara University campus in Mansehra, Pakistan. Experiments showed that the LPWAN technology is reliable, with 98% reliability, and suitable for implementing emergency response systems in smart campus environments.

Unveiling New IoT Antenna Developments: Planar Multibeam Metasurface Half-Maxwell Fish-Eye Lens with Wavelength Etching

This study introduces a groundbreaking antenna system, the directive Metasurface Half-Maxwell Fish-Eye (MHMF) lens antenna, tailored specifically for Internet-of-Things (IoT) networks. Designed to operate at 60 GHz, this antenna ingeniously integrates a dipole antenna within a parallel-plate waveguide to illuminate a Half-Maxwell Fish-Eye (HMFE) lens. The HMFE lens serves as a focal point, enabling a crucial high gain for IoT operations. The integration of metasurface structures facilitates the attainment of the gradient refractive index essential for the lens surface. By employing commercial Ansys HFSS software, extensive numerical simulations were conducted to meticulously refine the design, focusing particularly on optimizing the dimensions of unit cells, notably the modified H-shaped cells within the parallel waveguides housing the beam launchers. A functional prototype of the antenna was constructed using a standard PCB manufacturing process. Rigorous testing in an anechoic chamber confirmed the functionality of these manufactured devices, with the experimental results closely aligning with the simulated findings. Far-field measurements have further confirmed the effectiveness of the antenna, establishing it as a high-gain antenna solution suitable for IoT applications. Specifically, it operates effectively within the 60 GHz range of the electromagnetic spectrum, which is crucial for ensuring reliable communication in IoT devices. The directive HMFE lens antenna represents a significant advancement in enhancing IoT connectivity and capabilities. Leveraging innovative design concepts and metasurface technology, it heralds a new era of adaptable and efficient IoT systems.

IoT based Water Tank Cleaner using STM32

Water tanks are essential for storing and supplying clean water in both residential and industrial settings. However, over time, these tanks can accumulate sediment, algae, and other contaminants that can compromise water quality. Cleaning and maintaining water tanks is a critical task to ensure the supply of safe and clean water to consumers. The IoT-Based Water Tank Cleaner using STM32 project aims to address this issue by developing an innovative solution that automates the cleaning process of water tanks. This project leverages the power of the Internet of Things (IoT) and the capabilities of the STM32 microcontroller to create an intelligent and efficient water tank cleaning system. This project presents an innovative solution for water tank cleaning using the STM32 microcontroller and IoT (Internet of Things) technology. The proposed system automates the process of cleaning and monitoring water tanks, ensuring efficient operation and minimizing manual intervention. Water scarcity is a pressing global issue, necessitating efficient management of water resources. One significant aspect of water management is maintaining the cleanliness of water storage tanks, which often harbor contaminants due to neglect or inadequate cleaning procedures. This project introduces an IoT-based solution leveraging the STM32 microcontroller to automate the cleaning process of water tanks. The system employs sensors to monitor water quality, an actuator for tank cleaning, and IoT connectivity for remote monitoring and control. Key Words: Water tank cleaning, IoT-based solution, STM32, Water quality, Sediment removal

IoT Enabled Real Time Low Cost Cardiac Monitor Using LabVIEW

The rapid advancement of the Internet of Things (IoT) and medical technology has paved the way for innovative healthcare solutions. The system incorporates IoT connectivity to enable remote monitoring, data collection, and analysis, enhancing patient care and medical decision making. Cardiac monitoring system used in hospitals to measure and record the cardiac parameters. Vital parameters are transferred within the hospitals either using Wi-Fi or Bluetooth. Range of transmission for such wireless communication is only effective within the hospitals and further transfer to a long distance is limited. The proposed cardiac monitoring system is developed using LabVIEW environment - a versatile Graphical User Interface (GUI). Data acquired through the electrodes are connected to my DAQ Unit (Data Acquisition Unit) which helps to integrate electrodes with computer or PC. Data acquired from the Software is connected to the firebase console and it will help the practitioners to share the data in live and updated. It offers benefits such as early detection of cardiac irregularities such as arrythmia, reduced hospitalization periods, and improved patient outcomes. Additionally, healthcare practitioners and caretakers can remotely access patient data, enabling timely interventions and personalized treatment plans. Since the cardiac monitors are often used by bedside patients, it may introduce bed sores in them. Hence, in addition to these parameters, body moisture level and temperature of the patient are measured using DHT11(temperature and humidity sensor) to ensure the prevention of bedsores. These additional parameters measured are also enabled to view through IoT.

Enhanced EV Battery Monitoring Using IoT with Improved SEPIC - ZETA Converter and Modified Lion Optimization for Photovoltaic Systems

The rising popularity of electric vehicles (EVs) and the increasing emphasis on sustainable transportation have highlighted the importance of advanced monitoring systems. These systems play a crucial role in providing real-time information about battery parameters to ensure optimal performance and longevity. Moreover, the integration of renewable energy sources, specifically photovoltaic (PV) systems, with EV charging infrastructure presents an exciting prospect to enhance energy efficiency and minimize environmental harm. As a consequence the proposed work develops an Internet of Things (IoT) based PV fed EV charging system. The system incorporates an improved SEPIC-Zeta converter together with Modified Lion Optimization algorithm (LOA) assisted Proportional Integral (PI) controller for optimizing PV system for charging EV battery. IoT connectivity monitors parameter such as PV voltage, PV current, and State of Charge (SOC) of battery. Real-time monitoring of these parameters is achieved by leveraging sensors. The collected data is transmitted through IoT networks to a central monitoring system, enabling operators to track the performance of PV system and EV battery. This facilitates optimized energy generation, efficient battery charging and discharging, and overall system reliability. IoT-enabled monitoring system provides remote accessibility, data analytics, and the generation of alerts and notifications for timely actions. Experimental validation demonstrates that, the proposed concept enhances the monitoring capabilities, improves energy efficiency, and ensures reliable operation of EV charging infrastructure.

Next-Gen Medical Technology a Smart Approach to Syringe Injection Pump Automation

This presents the design, implementation, and successful validation of a cutting-edge IoT-based Syringe Injection Pump (SIP) for precision medication administration. In response to the increasing demand for enhanced healthcare automation, this system leverages technologies to address critical challenges in medication delivery. This SIP incorporates a robust Internet of Things (IoT) framework, enabling seamless communication between the device and a central healthcare management system. The automated syringe injection process is governed by a sophisticated algorithm that considers patient-specific parameters, ensuring precise dosage administration. Through extensive testing and real-world simulations, the results demonstrate a significant reduction in human error and improved medication adherence. The system’s architecture integrates secure communication protocols, ensuring data confidentiality and integrity during transmission. An innovative user interface provides healthcare professionals with real-time monitoring and control capabilities, enhancing situational awareness and responsiveness. Furthermore, the SIP’s adaptability to diverse medical environments underscores its versatility in meeting the evolving needs of healthcare institutions. To validate the system’s effectiveness, a comprehensive performance evaluations, including dosage accuracy, response time, and reliability under varying conditions was conducted. Results indicate an impressive dosage precision of 99.8%, showcasing the system’s reliability in critical healthcare scenarios. The IoT connectivity facilitates remote monitoring and control, allowing healthcare providers to intervene promptly in case of anomalies or emergencies. In addition to its technical prowess, the SIP aligns with current healthcare trends by promoting sustainability and cost-effectiveness. The automated system optimizes resource utilization, reduces medication waste, and minimizes the environmental impact associated with traditional manual injection methods. In conclusion, this IoT-based Syringe Injection Pump represents a paradigm shift in medical technology, offering a smart and results-oriented solution for precise medication administration. The successful implementation and validation of this system pave the way for improved patient outcomes, streamlined healthcare workflows, and a more sustainable approach to medication delivery. This research contributes to the ongoing discourse on advancing medical technology and underscores the potential of IoT in shaping the future of healthcare.