iosr-JECE   Volume-20 ~ Issue-3 ~ May - Jun. 2025

Abstract: A significant number of people who have impairments are dependent on other people for help with day-to-day activities, particularly with regard to mobility. Users in wheelchairs, in particular, often need assistance in order to operate their chairs. Their freedom may be increased via the use of a wheelchair control system that gives them the ability to control their mobility through the use of speech recognition technology. Microcontroller, motor control interface board, and Google Assistant are all components that are included into this system to provide voice command capabilities. Users are able to manoeuvre the wheelchair by just speaking orders to Google Assistant. These commands include turning left or right, going forward or backward, and turning left or right. Through the usage of this system, users are able to become more self-sufficient, the stress placed on carers is lessened, and they are given the ability to engage more actively in day-to-day life.

Keywords: ROS, Encoded motors, Health monitoring system, Sensors, Raspberry pi pico w, Buzzer.

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Abstract: This study presents a comprehensive intelligent vehicular safety and monitoring system designed within the Internet of Things (IoT) paradigm to enhance real-time driver and vehicle condition assessment. The proposed system integrates a heterogeneous network of sensors including alcohol detection, eye-blink monitoring, accelerometers, and GPS/GSM modules with edge-computing-enabled microcontrollers to provide continuous, real-time situational awareness. Leveraging machine learning algorithms, the system improves detection accuracy for critical events such as driver inebriation, fatigue-induced micro-sleep, and collision impacts, while minimizing false alarms in dynamic operational environments.......

Keywords: Internet of Things (IoT), Intelligent Vehicle Safety, Driver Fatigue Detection, Collision Detection, Edge Computing, Machine Learning, Embedded Systems, GSM/GPS Tracking, Telematics, Road Safety, Alcohol Detection, Real-Time Monitoring, Vehicular Surveillance, Microcontroller, Smart Transportation.

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Abstract: The rapid advancements in the power electronics sector have led to the evolution of multilevel inverters (MLIs) for various applications. Today, MLIs are preferred over conventional two-level inverters due to several advantages, such as lower voltage stress, reduced electromagnetic interference, and smaller filter size requirements. However, traditional MLIs often require a higher number of components to generate more voltage levels. To address this, this paper introduces a novel 7-level MLI with a reduced switch count, designed specifically for standalone energy systems. To efficiently control the system and reduce harmonics, a firefly-assisted Glowworm Swarm Optimization (GSO) algorithm is applied for selective harmonic elimination (SHE). The Moth-Flame Optimization (MFO) algorithm is utilized to eliminate low-order harmonics from the output voltage of the proposed MLI........

Keywords: Firefly algorithm (FA); multilevel inverter (MLI); selective harmonic elimination (SHE). GSO, MFO and PSO.

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