ArchGenTool: a System-Independent Collaborative Tool for Robotic Architecture Design

Complex robotic architectures require a collaborative effort in design and adherence to the design in the implementation phse. ArchGentTool is a collaborative architecture generation tool which supports the design of the robotic architecture in a multi-level fashion. It comprises high-level conceptual analysis of the system to be designed, as well as low-level implementation breakdown of its functional components, acting complementary to the ROS framework. The tool facilitates reusability and expandability of the architecture to any robotic system, as it can be adapted to different specifications. A case study with the RAMCIP service robot is presente

Malfunction diagnosis in industrial process systems using data mining for knowledge discovery

The determination of abnormal behavior at process industries gains increasing interest as strict regulations and highly competitive operation conditions are regularly applied at the process systems. A synergetic approach in exploring the behavior of industrial processes is proposed, targeting at the discovery of patterns and implement fault detection (malfunction) diagnosis. The patterns are based on highly correlated time series. The concept is based on the fact that if independent time series are combined based on rules, we can extract scenarios of functional and non-functional situations so as to monitor hazardous procedures occurring in workplaces. The selected methods combine and apply actions on historically stored, experimental data from a chemical pilot plant, located at CERTH/CPERI. The implementation of the clustering and classification methods showed promising results of determining with great accuracy (97%) the potential abnormal situations

An intelligent decision making and notification system based on a knowledge-enabled supervisory monitoring platform

This work describes a knowledge-based framework which is able to communicate online with process systems utilizing the existing infrastructure and provide knowledgeable actions to the operators. The proposed knowledge-enabled supervisory monitoring (KSM) platform combines components of existing standards such as ISA-95 in order to facilitate the data exchange between the automation system and the data repository. The functionalities of the developed platform are demonstrated using the requirements of an industrial control system of a continuous process and aim at the evaluation of the process and equipment performance based on predefined rules

A Gamification Engine Architecture for Enhancing Behavioral Change Support Systems

This paper presents a gamified framework designed to offer behavioural change support and treatment adherence services to people living with Dementia (PLWD), their caregivers and medical/social professionals

Anomaly Detection in Small-Scale Industrial and Household Appliances

Anomaly detection is concerned with identifying rare events/ observations that differ substantially from the majority of the data. It is considered an important task in the energy sector to enable the identification of non-standard device conditions. The use of anomaly detection techniques in small-scale residential and industrial settings can provide useful insights about device health, maintenance requirements, and downtime, which in turn can lead to lower operating costs. There are numerous approaches for detecting anomalies in a range of application scenarios such as prescriptive appliance maintenance. This work reports on anomaly detection using a data set of fridge power consumption that operates on a near zero energy building scenario. We implement a variety of machine and deep learning algorithms and evaluate performances using multiple metrics. In the light of the present state of the art, the contribution of this work is the development of a inference pipeline that incorporates numerous methodologies and algorithms capable of producing high accuracy results for detecting appliance failures