Review on IOT-Based Industrial Automation System - Rathore, Rakesh; Bhiwapurkar, Prof. Himanshu; Chougaonkar, Prof. Anagha; Carpenter, Prof. Umesh (INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT, 2025)
Nowadays industrial automation has evolved from basic mechanization to sophisticated, interconnected systems driven by the Industrial Internet of Things (IIoT), artificial intelligence, and low-cost microcontroller platforms. This review examines the integration of Arduino Mega 2560 and NodeMCU ESP8266 microcontrollers with industrial sensors, actuators, and cloud-based monitoring via ThingSpeak, enabling real-time object drilling, material classification (metal vs. non-metal), and color detection applications. Key technologies—including inductive and capacitive proximity sensors, TCS3200 color sensors, stepper-motor-driven conveyor systems, and AI/ML-enhanced control—are analyzed for performance, scalability, and industrial suitability. Market trends indicate the IIoT installed base will nearly double from 56.5 million devices in 2023 to 110.3 million by 2028, while the global IIoT market is projected to exceed $286 billion by 2029. Challenges such as electromagnetic interference, vibration resilience, IP protection, protocol standardization, and cybersecurity are discussed alongside emerging solutions, including industrial-grade Arduino PLCs, edge computing, and digital twins. Finally, future research directions are identified to advance real-time AI/ML decision-making, enhance interoperability, and develop robust, energy-efficient automation systems—paving the way for broader adoption of Arduino-based smart manufacturing in the era of Industry 4.0. Keywords:  Internet of Things, Stepper Motor, ThingSpeak, ESP32, ESP-32, Arduino, Metal Detector, Color Sensor, Drilling Machine