Journal of Control Systems and Converters

Intelligent Process Control Approach for Smart Waste Handling in Manufacturing Industries

Suriyaprabha Ka. — 2026-06-19

The rapid industrialization and growing waste generation in manufacturing environments have presented substantial challenges in waste management and environmental sustainability. Conventional waste management systems depend primarily on manual segregation, which is susceptible to contamination, low recycling rates, health hazards for workers and increased operational costs. To tackle these issues, this paper proposes a process control approach for smart waste handling in manufacturing units with an automated waste segregation smart dustbin system. The proposed system is an intelligent decision-making and automated segregation system that integrates multiple sensors like moisture sensors, infrared sensors, ultrasonic sensors and inductive proximity sensors with an Arduino Uno microcontroller. Waste materials are analyzed based on physical characteristics in real time, and a servo motor mechanism directs the waste into appropriate biodegradable or non-biodegradable compartments. Further, the ultrasonic sensors monitor the fill levels of bins continuously. Also, a GSM module is used to send remote alerts for proper waste collection and maintenance. The system also comprises efficient power management techniques and is designed to support future integration with the IoT and solar energy systems. The experimental analysis shows a global accuracy for segregation of about 92.7% with a robust real-time performance. The proposed smart waste handling framework enhances operational efficiency, reduces manual intervention, improves worker safety and enables sustainable waste management practices in modern manufacturing environments.

Cruise System for Electric Bicycle with Bluetooth-Based Auxiliary Functions

A. Kalyan Kumar — 2026-06-24

This paper presents the design and implementation of a cruise system for an electric bicycle integrated with Bluetooth-based auxiliary functions. The proposed system enables automatic speed locking when the rider maintains a constant throttle position for a predefined duration, thereby eliminating the need for continuous throttle input and reducing rider fatigue during long-distance travel. The cruise functionality is implemented using a standard BLDC motor controller, ensuring stable and efficient speed regulation under practical operating conditions. In addition to cruise control, a Bluetooth module is incorporated to provide wireless control of auxiliary features such as key ON/OFF, headlight operation, and horn activation through a mobile application. The cruise system and auxiliary control system operate independently, ensuring safety, reliability, and uninterrupted performance. The system continuously monitors brake and throttle inputs and automatically deactivates cruise mode when braking is applied or when any variation in throttle position is detected. Experimental results demonstrate that the proposed system maintains consistent speed and performs reliably under varying load conditions. The overall design is simple, cost-effective, and suitable for real-time implementation, making it an effective solution for enhancing performance and user convenience in modern electric bicycles.

Smart Agricultural Drone with AI Pest Detection and Spraying Mechanism

Priya Singh — 2026-06-25

This paper presents the design and development of a smart agricultural drone integrated with artificial intelligence (AI) for real-time pest detection and automated pesticide spraying. The proposed system combines unmanned aerial vehicle (UAV) technology with computer vision and machine learning algorithms to enable efficient crop monitoring and precision farming. The drone captures high-resolution images of agricultural fields, which are processed using trained models to identify pest-infested regions with high accuracy. Based on the detection results, a targeted spraying mechanism is activated to apply pesticides only in affected areas, thereby reducing excessive chemical usage and minimizing environmental impact. The system is designed to operate autonomously, reducing manual intervention and improving operational efficiency in large-scale farming environments. Furthermore, the selective spraying approach optimizes resource utilization, lowers input costs, and enhances crop productivity. The integration of AI-driven decision-making with UAV-based monitoring demonstrates a scalable and sustainable solution for modern agriculture. The proposed approach contributes to the advancement of smart farming technologies by improving yield, ensuring environmental safety, and supporting data-driven agricultural practices.

Design and Implementation of a Traffic Light Controller using FSM in Verilog

Akash — 2026-07-09

As traffic density continues to rise in urban and suburban areas, the role of an efficient traffic light control system becomes increasingly significant in maintaining smooth vehicle movement and reducing congestion. Traffic signals are essential components of transportation infrastructure because they regulate the movement of vehicles and pedestrians at road intersections. Conventional traffic systems often operate with fixed timing sequences that may not effectively adapt to changing traffic conditions. Therefore, designing a structured and reliable traffic control mechanism is necessary for improving traffic efficiency and road safety. One practical approach for achieving this is through the implementation of a traffic light controller using Finite State Machines (FSM) and Verilog Hardware Description Language (HDL). FSM provide a systematic method for representing and controlling sequential behavior in digital systems. An FSM operates by transitioning among a set of predefined states according to specific conditions or inputs. In a traffic light controller, the system can be divided into different states representing the signal conditions, such as red, yellow, and green lights. Each state performs a specific function and remains active for a defined duration before moving to the next state. The transition between these states follows a logical sequence that ensures organized traffic movement and prevents conflicting signals. By using FSM methodology, the traffic light system becomes easier to design, analyze, and verify due to its predictable behavior and structured operation. The design process begins by defining the states and establishing the transition rules based on timing parameters. For example, a green light state allows vehicles to move; the yellow light serves as a warning period before the signal changes, and the red light instructs vehicles to stop. Timing control plays a critical role in determining how long each signal remains active. The FSM monitors the current state and, based on the timer conditions, shifts to the subsequent state in the sequence. This state-based operation improves the reliability and efficiency of the traffic management system. Simulation helps identify design errors and verify whether the traffic light system behaves according to the expected sequence and timing requirements. The combination of FSM and Verilog HDL provides a practical and efficient solution for traffic light controller design. FSM ensures organized state transitions, while Verilog enables hardware-level implementation and simulation. Through simulation and analysis, the designed system can be evaluated for accuracy and performance before real-world implementation. This approach contributes to developing a reliable traffic management system capable of handling increasing traffic demands while ensuring safety and efficiency at road intersections.

Rapidly Inflate Airbags During Collision and Automatic Alert System

Yogesh B. Bangale — 2026-07-20

Accidents are one of the major causes of injuries and fatalities across the world, especially in road transportation, industrial workplaces, and elderly care environments. Conventional safety systems mainly focus on passenger protection inside vehicles and often fail to provide immediate emergency communication after an accident. This paper presents a smart rapid airbag deployment and automatic alert system designed to enhance safety and reduce injury severity during collision events. The proposed system integrates an ESP32 microcontroller, MPU6050 MEMS sensor, GPS module, GSM communication module, and a CO₂-based inflation mechanism for intelligent accident detection and emergency response. The MPU6050 sensor continuously monitors acceleration and vibration data to identify abnormal motion or collision conditions. When the detected acceleration exceeds the predefined threshold value, the system instantly activates the airbag deployment mechanism and sends the accident location to emergency contacts through GSM communication. The proposed system can be used in vehicles, elderly care systems, occupational safety equipment, and wearable protection devices. A prototype of the proposed system was successfully developed and integrated using ESP32, MPU6050, GPS, GSM, and a CO₂-based inflation mechanism. The system continuously monitors acceleration and vibration data to identify abnormal motion conditions and automatically initiates airbag deployment and emergency communication. The developed prototype demonstrates the feasibility of integrating accident detection, rapid protection, location tracking, and alert transmission into a unified safety platform. The proposed solution can be adapted for vehicle safety, elderly care, industrial safety, and wearable protection applications. Future work will focus on large-scale experimental validation, deployment performance evaluation, and AI-based impact classification.