Anomaly detection is a problem with applications for a wide variety of domains; it involves
the identification of novel or unexpected observations or sequences within the data being …

The so-called “smartization” of manufacturing industries has been conceived as the fourth
industrial revolution or Industry 4.0, a paradigm shift propelled by the upsurge and …

Faults in photovoltaic (PV) systems, which can result in energy loss, system shutdown or
even serious safety breaches, are often difficult to avoid. Fault detection in such systems is …

This study reports the development of an innovative fault detection and diagnosis scheme to
monitor the direct current (DC) side of photovoltaic (PV) systems. Towards this end, we …

To promote sustainable development, the smart city implies a global vision that merges
artificial intelligence, big data, decision making, information and communication technology …

This paper presents a model-based anomaly detection method for supervising the direct
current (dc) side of photovoltaic (PV) systems. Toward this end, a framework combining the …

Data mining (DM) is an instrument of pattern detection and retrieval of knowledge from a
large quantity of data. Many robust early detection services and other health-related …

Energy consumption is vital to the global costs of wastewater treatment plants (WWTPs).
With the increase of installed WWTPs worldwide, the modeling and forecast of their energy …

A systematic approach for monitoring road traffic congestion is developed to improve safety
and traffic management. To achieve this purpose, an improved observer merging the …

Precision machining tool wear is responsible for low product throughput and quality.
Monitoring the tool wear online is vital to prevent degradation in machining quality …