Innovations in Biomedical Engineering: Advancing Healthcare Devices on Recent Technology
Flood Detection and Monitoring using Arduino Based Sensor Technology
Automatic Lower Limb Rehabilitation Device
Heart Rate Variability-Based Detection of Driver Drowsiness and its Validation using EEG
IoT-Enabled Smart Shoes for the Blind
Biosensors for Early Diagnosis and Automated Drug Delivery in Pancreatic Cancer
Verilog Based UART System Design
Intel ® Processor Architectural and Integrated Development Environment Exploration
IoT based Smart Agriculture Monitoring Framework with Automation
An Integrated Model of Digital Fuel Indicator and GPS Tracking System for Vehicles
Designing of an Embedded system for Wireless Sensor Network for Hazardous Gas leakage control for industrial Application
Hardware Implementation of Artificial Neural Networks
Fault Analysis on Grid Connected MPPT BasedPhotovoltaic System
High Efficiency Hybrid Intelligent Street Lighting Using A Zigbee Network And Sensors
Design of Dual-Band Bandpass Filter Using Interdigital Embedded Open Loop Triangular Resonator Loaded with Stubs
License Plate Localization Using Novel Recursive Algorithm And Pixel Count Method
Root canal treatment is a treatment sequence for the infected pulp of a tooth which is intended to result in the elimination of infection and the protection of the decontaminated tooth from future microbial invasion. During root canal treatment, it is possible that the gutta-percha cones, which are a permanent filling in the treatment, become contaminated. Before being placed in the root canal, it must be sterilized. Additionally, the gutta-percha sterilization process may lead to bacterial growth in the root canal. Thus, gutta-percha sterilization should take place at the same time as root canal cleaning. For this purpose, gutta-percha sterilization must be automated, instead of conventional disinfection methods. The primary objective of this study is to automate the gutta-percha sterilization operation and improve disinfection efficacy with a low turn-around time and high precision. As per the results obtained during the experiment, the turn-around time for sterilization takes 5-8 minutes with good disinfection efficacy in microbial testing and a precision of 92% for 57 cycles of testing.
An automatic railway gate control system using an Arduino UNO and IR sensors is proposed in this study. The manually operated rail gates can be converted into automatic control of railway gates using different types of sensors. These are mostly needed where the track passes over a city, neighborhood, or redundant gateways of the passage regions. The gates are currently manually operated by gatekeepers according to the existing system, depending on signals obtained from the control centre. Accidents are most likely to occur in such cases, causing severe loss of human lives and property near rail crossing zones. The programmed railway gate regulator tracks the movement of the train and detects obstacles, thereby notifying the server motor to open or close the gate automatically. This study also suggests the effective use of real-time information on the train positions. The main objective of this study is to safeguard efficiency, quality, time management, public safety and automation.
The use of Wireless Sensor Networks (WSNs) has become increasingly popular in agriculture for real-time monitoring of environmental parameters. This study presents the development and evaluation of a WSN implemented using Arduino, Raspberry Pi, and XBee modules for real-time monitoring of temperature, humidity, soil moisture, and light intensity in a greenhouse. The results demonstrate that the system provides reliable and accurate data with low power consumption, thereby highlighting the feasibility of using WSNs for agricultural monitoring. This substantiates the feasibility and practicality of employing WSNs as invaluable tools for agricultural monitoring. As agriculture undergoes a transformative shift towards precision and sustainability, this research underscores the potential of WSNs to revolutionize farming practices, enhance resource allocation, increase crop yields, and ultimately contribute to the promotion of environmentally responsible agriculture. This study serves as a significant step in the convergence of technology and agriculture, fostering more efficient and eco-conscious farming methodologies.
Energy conservation is a key challenge for a sustainable lifestyle. However, it is often ignored because of a lack of knowledge and inability to predict the lifetime of electric or electronic equipment. Energy conservation is the most cost-effective strategy for coping with energy shortage. This study proposes the implementation of e-Life devices to solve this problem and promote public awareness. Electricity-intensive products have their own power specifications and lifespans; over time, the amount of power they use is greater than expected because of the effects of aging. The e-Life algorithm used in an Internet of Things (IoT)-enabled electronic device is integrated into any electrical load to monitor power usage and understand the product replacement time. It is proposed to be aware of the excessive power consumption of all-electric or electronic equipment.
A biosensor is an analytical device containing immobilized biological materials (enzymes, antibodies, nucleic acids, hormones, organelles, or whole cells) that can specifically interact with an analyte and produce physical, chemical, or electrical signals that can be measured, and then report these data and use them for medical applications. Biosensors have transformed diverse fields, including medical diagnostics to diagnose infectious diseases, environmental monitoring, and food safety, by enabling rapid, sensitive, and selective detection of target analytes. This study provides a comprehensive review of biosensor technology, covering the fundamental principles and practical applications. Recent advances in biological techniques and instrumentation involving fluorescence tags for nanomaterials have increased the sensitivity of biosensors. The current challenges and future prospects are also discussed in this study.
