Temperature and Humidity Measurement of Baby Incubator using PSoC CY8CKIT-062-WiFi-BT
Implementation of Position Sensorless Brushless DC Motor Drive
Guardians of the Green: Revolutionizing Irrigation with Sensor Intelligence
Solar Panel Dry Cleaning Robot
Adaptive Rise the Economical Height - Adjustable Wheelchair
Integration of Medical Devices using Internet of Things
Diagnosis of Air-Gap Eccentricity Fault for Inverter Driven Induction Motor Drives in the Transient Condition
Modelling and Simulation Study of a Helicopter with an External Slung Load System
Comparative Study of Single Phase Power Inverters Based on Efficiency and Harmonic Analysis
LabVIEW Based Design and Analysis of Fuzzy Logic, Sliding Mode and PID Controllers for Level Control in Split Range Plant
Trichotomous Exploratory Data Analysis [Tri–EDA]: A Post Hoc Visual Statistical Cumulative Data Analysis Instrument Designed to Present the Outcomes of Trichotomous Investigative Models
This work deals with the development of a temperature and humidity monitoring system designed specifically for neonatal intensive care units (NICUs), which serve as dedicated spaces for premature or fragile newborns. These units aim to replicate the conditions of a mother's womb, essential for the survival and growth of vulnerable infants. Maintaining proper thermoregulation is critical, as failure to do so remains a significant, yet preventable, cause of mortality among neonates. For premature and delicate infants, consistent body temperature is vital for optimal development. This paper focuses on monitoring and regulating the temperature and humidity levels within the NICU, as these factors play a key role in the well-being of preterm infants. The system utilizes a set of specialized sensors, with the collected analog signals processed through a peripheral interface controller to ensure efficient monitoring.
The implementation of a position sensorless drive for Brushless DC (BLDC) motors enhances reliability, reduces cost, and improves compactness in motor control systems. This study develops a control strategy that eliminates physical position sensors by estimating rotor position through back electromotive force (BEMF) and zero-crossing detection. Advanced techniques such as Phase Locked Loops (PLL) and Sliding Mode Observers (SMO) are applied for accurate commutation under variable load and speed. The system was implemented using a low-cost microcontroller, and experimental validation was conducted to compare performance before and after sensorless integration. Results showed a dust removal efficiency of 94.2%, a reduction in cleaning duration by 18%, and energy consumption per cleaning cycle of 0.025 kWh. Testing was conducted under standard ambient conditions (25°C, 1.01 atm) on a 250 W BLDC motor. Simulation and experimental analysis demonstrated smooth startup, steady-state behavior, and a rotor speed error margin below 3% compared to Hall-sensor-based control, validating the effectiveness of the sensorless design.
Water scarcity and inefficient irrigation remain major challenges in sustainable agriculture. This paper presents a smart irrigation system that integrates DHT11, soil moisture, rain, and water level sensors with an ESP32 microcontroller and Random Forest Algorithm for data-driven irrigation control. Real-time data is transmitted to the ThingSpeak cloud for remote monitoring. The system achieved 62% precision in identifying irrigation needs and reduced manual intervention while conserving water. By optimizing water usage, lowering costs, and enhancing yield, the proposed system offers a scalable and eco-friendly solution for modern farming.
Solar panels are highly dependent on sunlight exposure for optimal energy production. However, dust and debris accumulation on panel surfaces significantly reduce their efficiency, especially in arid and dusty environments. Traditional cleaning methods are labor intensive and may involve significant water usage or require chemical agents, leading to increased operational costs and environmental concerns. To address these issues, this paper presents a design for an autonomous dust cleaning robot specifically tailored for solar panels. The proposed robot is equipped with sensors, cleaning mechanisms, and a lightweight structure that ensures safe and efficient operation without damaging the panels. The system utilizes automated brushes or an air blast system powered by minimal energy, which can be sourced directly from the solar panels. By employing an intelligent cleaning schedule based on dust density and weather patterns, this robot minimizes power loss due to dust and reduces maintenance costs. Initial field tests demonstrate that the cleaning robot effectively restores panel efficiency, presenting a sustainable solution to the ongoing issue of solar panel soiling.
Wheelchairs have advanced to improve mobility for individuals with disabilities, yet many affordable options lack essential features that ensure comfort and adaptability for extended use. This paper focuses on creating a cost-effective, electrically powered wheelchair that combines height adjustment, a reclining mechanism for transitioning into a flatbed position, and innovative features such as weight measurement, a leg massager, and an integrated toilet accessibility system. These enhancements aim to foster greater independence and reduce reliance on external support. The versatile design allows users to seamlessly transition between sitting, lying, and adjusted height positions while also enabling effortless movement through an electric drive system. By making these advanced features more accessible, the wheelchair aims to enhance users' quality of life, improve mobility, and alleviate the workload of caregivers, contributing to a more inclusive and adaptable healthcare system.
Medical Devices Integration (MDI) helps healthcare organizations manage data more effectively and streamlines both clinical and administrative activities. When doctors have real-time access to the latest patient data, they can make more informed decisions regarding diagnosis and treatment. MDI can be achieved through software-based healthcare applications or direct integration of two or more medical devices. It plays a vital role in enhancing patient care by enabling seamless data exchange between medical devices and Electronic Health Records (EHR). Leveraging the Internet of Things (IoT), MDI offers several benefits, including improved data accuracy, streamlined workflows, enhanced communication among healthcare professionals, timely alerts for critical conditions, and ultimately, better patient outcomes through comprehensive real-time information access.
