Industrial internet of things (IIoT) has ushered us into a world where most machine parts are
now embedded with sensors that collect data. This huge data reservoir has enhanced data …

In an industrial setting, consistent production and machine maintenance might help any
company become successful. Machine health checking is a method of observing the status …

The use of IoT has become pervasive and IoT devices are common in many domains.
Industrial IoT (IIoT) utilises IoT devices and sensors to monitor machines and environments …

The starve of optimized solutions through Artificial Intelligence and broadening its scope in
machine health monitoring through diversified machine learning methods got significance …

The genesis of artificial intelligence, edge and fog computing has radiated their scope to
harmonize with any sector, ranging from medical to manufacturing industries. Amongst …

Data-driven predictive maintenance (PM) is an approach that leverages advanced analytics,
artificial intelligence (AI), and sensor data to predict when equipment failure might occur …

Predictive maintenance is the process of monitoring equipment continuously during its
operation to monitor its performance to report its faults beforehand. Using machine learning …

Edge analytics is an approach to data collection and analysis in which an automated
analytical computation is performed on data at a sensor, network switch or other devices …

The application of Artificial Intelligence (AI) approaches in industrial maintenance for fault
detection and prediction has gained much attention from scholars and practitioners. This …

Industry 4.0, allied with the growth and democratization of Artificial Intelligence (AI) and the
advent of IoT, is paving the way for the complete digitization and automation of industrial …