Embedded Systems

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.