Internet of Things

The growing concern over ineffective waste management in rapidly urbanizing areas has continued to threaten environmental sustainability, public health, and urban aesthetics— particularly in developing nations such as Nigeria. Conventional waste collection methods, which rely on manual inspections, static collection schedules, and minimal automation, are increasingly inadequate for modern cities. These traditional systems often result in overflowing waste bins, unhygienic surroundings, and increased exposure of sanitation workers to hazardous waste. To mitigate these challenges, the adoption of smart waste management systems has become a practical solution, harnessing Internet of Things (IoT) technologies to enhance operational efficiency, reduce health risks, and support global sustainability goals. This project presents the design and development of an improved smart dustbin system, which integrates sensors, automation, and wireless communication for efficient and hygienic waste collection. The system was engineered to address major limitations of existing smart waste bin models—such as lack of automation, low adaptability to environmental conditions, and poor sustainability—by introducing enhanced features that improve functionality, reliability, and user safety. The prototype incorporates ultrasonic sensors for detecting the fill level and load cell sensors for measuring the weight of accumulated waste. These sensors interface with an Arduino microcontroller, which interprets real-time data and initiates corresponding control actions. A key innovation in this design is the dual alert and communication mechanism, facilitated by a GSM module (SIM900D) that transmits SMS notifications and also initiates automated phone calls to designated waste management personnel once the bin reaches its full capacity. In addition, the system integrates a GPS module that tracks the exact location of the bin, simplifying collection logistics and enabling efficient route planning. To further enhance automation, the system features a linear actuator that performs self-compaction, reducing the waste volume and increasing the storage capacity before the next collection. Importantly, once the waste bin reaches its maximum threshold, the lid is automatically locked, preventing further deposit of waste and ensuring cleanliness until the bin is emptied and reset for operation. This mechanism helps prevent overflow and reduces contact with potentially contaminated waste. The system is powered by a 24W rechargeable lithium battery supported by a DC–DC converter, ensuring stable power supply and efficient energy usage. The software component was developed using Embedded C/C++ on the Arduino IDE, enabling real-time sensor monitoring, threshold detection, and GSM/GPS communication control. Comprehensive testing was carried out to evaluate sensor accuracy, power efficiency, communication reliability, and the responsiveness of the compaction and locking mechanisms. Results from both hardware and software testing confirmed that the system achieved reliable waste level detection, efficient data transmission, timely alert notifications, and effective compaction cycles. The automatic locking feature also performed accurately, preventing waste input once the bin reached capacity. By combining IoT technology, automation, and sustainable material selection, the improved smart dustbin system demonstrates a viable, scalable, and eco-friendly approach to modern waste management. Its ability to autonomously monitor fill levels, compress waste, lock when full, and communicate through both SMS and phone calls significantly enhances efficiency, hygiene, and sustainability. This prototype provides a foundation for large-scale implementation in residential, institutional, commercial, and municipal environments, contributing to cleaner cities and smarter waste management systems that align with sustainable development goals.

This study presents the design and fabrication of a Smart Internet of Thing (IoT)-based feul monitoring system for agricultural tractors. The system aims to improve operational efficiency, minimize fuel theft, and enhance real-time decision-making in mechanized farming. It integrates an ultrasonic fuel level sensor, NodeMCU V3 microcontroller, GPS, and GSM modules to provide continuous fuel data and location tracking. Using Blynk and Thing Speak IoT platforms, real-time fuel levels, consumption trends, and geographic positions were displayed through web and mobile interfaces. Calibration and testing revealed that the system achieved high measurement accuracy with an error margin of less than ±5%, Wi-Fi data transmission latency between 6–8 seconds, and SMS alert delay of 7–12 seconds. The prototype demonstrated effective performance under field conditions, withstanding vibration, heat, and moisture without data loss. Results confirm that the developed IoT-based system is affordable, reliable, and user-friendly for small- and medium-scale farmers. It enables efficient monitoring of fuel resources, enhances accountability, and supports preventive maintenance through analytics and alert mechanisms. Overall, the system bridges the technological gap in fuel management for agricultural operations in developing regions and contributes to sustainable mechanization practices.

The aim of this paper is to design and develop an IoT based Smart Monitoring System. The purpose of the current method is to create a safe and secure fish farming that helps the fish pond owners in producing high quality fish by maintaining normal water levels in the fish tank. (Sajal Saha, 2007). In order to implement this design, the Atmega 328p microcontroller is used as well assensors and actuators such as the DSB18b20 temperature sensor, HC-sr04 ultrasonic sensor, HC- sr501 motion sensor and a solenoid valve to automate the process of controlling the water quality parameters, such as the water level, temperature which is best at 24-27 oc (Johnson et al.,2007) and PH range which is acceptable at 6.5 to 9.0 (Will Mosley, 2009). These sensor values are stored in cloud so that farmers can see on their mobiles through mobile app or web application anywhere remotely. Android phone is used as the terminal device. A user can monitor the water condition using an android app through Wi-Fi within Wi-Fi range of 2400-2484 MHz and through Internet from anywhere in the world, A significant cost reduction is achieved as a result of farm equipment and water pumps being operated only when required using optimization schemes to maintain desired waterlevel in fish tank with efficient energy consumption through appropriate selection of pumps and tank filling level (Nirosha et al, 2017). The system consists of various sensors that measure important factors of the water like temperature, pH and water level and the data from these sensors can be accessed by an application through firebase (Weber et al, 2010). The farmer can then act as per the information relayed or the model can automatically act on behalf of the farmer as per the predefined actions. The real time information enables timely intervention by the farmers which eventually helps minimizing or eliminate wastages.

The increasing adoption of smart home technologies and the demand for robust home security systems have driven the need for innovative solutions that integrate various components seamlessly. This project presents a comprehensive smart home security solution that integrates IoT technology with remote camera control capabilities, leveraging the cost-effective ESP32-
CAM microcontroller. The system comprises two key components: a responsive web application and a Telegram bot interface, designed to provide homeowners with real-time surveillance and control functionality. The ESP32-CAM module, equipped with Wi-Fi connectivity and an integrated camera sensor, is the core hardware, capturing high-quality images and video streams
that can be accessed remotely through either interface. The web application offers an intuitive dashboard for monitoring live video feeds, viewing captured images, controlling camera parameters, and receiving motion-triggered alerts. Complementing this, the Telegram bot provides similar functionality through a conversational interface, allowing users to request images, view live streams, and receive instant notifications on their mobile devices. This dual-interface approach ensures accessibility across various devices and user preferences. The implementation utilizes a decentralized architecture where the ESP32-CAM operates as both a camera and a lightweight server, communicating directly with client applications without relying on cloud infrastructure. This edge computing approach prioritizes data privacy and reduces dependency on external services. The Telegram bot integration leverages the Telegram API for secure notifications while maintaining the local processing paradigm. Experimental
results demonstrate the system's effectiveness in providing reliable surveillance with minimal latency while maintaining reasonable power consumption for extended operation. This solution offers an affordable yet robust alternative to commercial smart security systems, making home security technology more accessible to a broader range of users