Journal of Microprocessor and Microcontroller Research

IoT-based Smart Multi-floor Parking Slot Detector System

M. Kamaraju — 2026-05-02

Due to extreme urbanization and a massive increase in vehicle size, parking management has become increasingly difficult in modern cities. Specifically, problems arise due to rapid growth rates of new multi-floor parking complexes such as malls, hospitals, airports, smart commercial buildings, etc. Problems caused by poor parking management may include traffic congestion, wasted fuel, CO₂ emissions, customer dissatisfaction, and so on, all as a result of drivers spending a large amount of time searching for available parking spots. Existing parking management systems use manual supervision or static signboards to provide drivers with parking spot availability information, and therefore are unable to provide real-time, floor-level parking availability information. The overall goal of this project is to create a system that will allow drivers to locate available parking spots quickly and accurately using Arduino, IoT, and embedded systems technology. The proposed solution is an IoT-based embedded multi-floor parking slot finder system—a system based on the use of IoT-enabled sensors, such as ultrasonic or infrared sensors, to continuously monitor the presence of vehicles parked in each parking space. The data from the sensors will be processed by the embedded controller and sent wirelessly to a centralized server or cloud service. The system will provide the capability to monitor multiple floors at once in a multi-floor parking complex, therefore allowing for accurate monitoring of every available parking slot, regardless of how many floors there are in the complex. Users will be able to access the current state of parking slots and receive directions to available parking slots via an online application or mobile application. The result will be a significant reduction in both the amount of fuel spent and the amount of time and distance that drivers travel when they are searching for available parking.

Voice-controlled Home Automation Using Arduino Nano, Bluetooth Communication, and MIT App Inventor

Ajit S. Naik — 2026-06-06

This study presents the design, simulation, and experimental prototype of a voice-controlled home automation system that enables users to operate household electrical appliances—including a light and a DC fan—using natural speech commands transmitted from a smartphone via Bluetooth. The system architecture comprises an Arduino Nano microcontroller (ATmega328P), an HC-05 Bluetooth serial module, a single-channel relay module, and a custom Android application developed using MIT App Inventor. The mobile application performs speech-to-text conversion natively on the smartphone and transmits the resulting text string to the Arduino via the HC-05 module at 9600 baud. The Arduino firmware parses incoming commands and actuates the relay to switch connected appliances accordingly. The system operates entirely offline, with no dependence on internet connectivity or cloud-based services, making it particularly suitable for rural and low-connectivity environments. During laboratory testing, the system demonstrated consistent command recognition for instructions such as "Turn on light" and "Turn off fan" with high accuracy and response latency below one second, maintaining a stable Bluetooth connection within a range of approximately 10 metres. The complete prototype was realised at a component cost of ₹3,600, significantly undercutting commercial smart-home alternatives while delivering equivalent core functionality for basic home automation. The system’s modular design supports straightforward expansion to additional appliances, IoT connectivity, and enhanced machine learning-based speech recognition in future iterations.

Fingerprint-based Biometric Attendance System using ESP32

Vikram D. Deshmukh — 2026-06-06

The Biometric Attendance System is a modern and efficient solution designed to automate the process of recording attendance using biometric technology such as fingerprint recognition, facial recognition, or iris scanning. Traditional attendance methods like manual registers and ID cards are time-consuming, less secure, and prone to errors or proxy attendance. This system overcomes these limitations by providing accurate, fast, and secure attendance management. The system follows a three-tier architecture consisting of the hardware layer, network layer, and application layer. Attendance records are securely stored in the cloud and can be monitored through a web dashboard and admin portal. Experimental results show that the system achieves high accuracy with low false acceptance and rejection rates, fast verification time, and reliable real-time performance. Compared to traditional manual attendance methods, the biometric system significantly reduces proxy attendance, data entry errors, and report generation time. Traditional manual and card-based attendance systems are plagued by proxy attendance, data tampering, and administrative overhead. This paper presents the design and implementation of a fingerprint-based biometric attendance system using the ESP32 microcontroller integrated with the AS608 optical fingerprint sensor. The proposed system captures and verifies fingerprint templates locally on the ESP32, records timestamped attendance entries, and synchronises data to a cloud database in real time via Wi-Fi. Experimental results demonstrate a False Acceptance Rate (FAR) of 0.02%, a False Rejection Rate (FRR) of 0.08%, an average verification response time of 1.2 seconds, and a 97.4% reduction in proxy-attendance incidents compared to manual registers. The system offers a cost-effective, accurate, and scalable alternative to conventional attendance management in academic institutions.