scholarly journals Formal Verification of Control Modules in Cyber-Physical Systems

Sensors ◽  
2020 ◽  
Vol 20 (18) ◽  
pp. 5154
Author(s):  
Iwona Grobelna
Keyword(s):  
Formal Verification ◽  
Automation System ◽  
Logical Model ◽  
Physical Systems ◽  
Verification Method ◽  
Manufacturing Automation ◽  
Abstract Rule ◽  
User Friendly ◽  
Control Modules

The paper proposes a novel formal verification method for a state-based control module of a cyber-physical system. The initial specification in the form of user-friendly UML state machine diagrams is written as an abstract rule-based logical model. The logical model is then used both for formal verification using the model checking technique and for prototype implementation in FPGA devices. The model is automatically transformed into a verifiable model in nuXmv format and into synthesizable code in VHDL language, which ensures that the resulting models are consistent with each other. It also allows the early detection of any errors related to the specification. A case study of a manufacturing automation system is presented to illustrate the approach.

scholarly journals Data-driven occupant-centric rules of automated shade adjustments: Luxembourg case study

2021 ◽  
Vol 2042 (1) ◽  
pp. 012126
Author(s):  
Ghadeer Derbas ◽  
Karsten Voss
Keyword(s):  
Environmental Parameters ◽  
Rate Of Change ◽  
Automation System ◽  
Building Management ◽  
Robust Control System ◽  
Building Management System ◽  
Office Rooms ◽  
User Friendly ◽  
Indoor And Outdoor

Abstract This study presents key findings of observed datasets in a nearly zero-energy office building for over 66 working days from June to mid-September in 2019, Luxembourg. Measurements of indoor and outdoor environmental parameters as well as user-shade override adjustments were extracted from the KNX-based building management system (BMS) in 47 office rooms located in three typical floor levels. Relative frequency and “rate of change” of blind use were analysed in terms of window orientation, occupancy level, and the time of the day. Logistic regression and data mining techniques were used to identify potentially useful and understandable occupant behaviour patterns and reveal the main triggers behind blind adjustments. The well-designed automation system together with the inner glare protection formed the base of very low user-shade interactions. A mean of 0.184 manual blind adjustments per day per office. Eight regression sub-models were developed and all were incapable of predicting user-shade lowering and raising events. Alternatively, two user profiles were mined based on 20 rules gained from clustering analysis: user (ß) was representing the passive user, and user (μ) the medium user. Overall, we conclude that the automated shading system in this building is satisfactory, user-friendly, and a robust control system.

Optimales Layout einer Walderschliessung

2016 ◽  
Vol 167 (5) ◽  
pp. 294-301
Author(s):  
Leo Bont
Keyword(s):  
Road Network ◽  
Spatial Arrangement ◽  
Problem Situation ◽  
Optimal Layout ◽  
Forest Road ◽  
The Road ◽  
Network Cost ◽  
User Friendly ◽  
Short Time

Optimal layout of a forest road network The road network is the backbone of forest management. When creating or redesigning a forest road network, one important question is how to shape the layout, this means to fix the spatial arrangement and the dimensioning standard of the roads. We consider two kinds of layout problems. First, new forest road network in an area without any such development yet, and second, redesign of existing road network for actual requirements. For each problem situation, we will present a method that allows to detect automatically the optimal road and harvesting layout. The method aims to identify a road network that concurrently minimizes the harvesting cost, the road network cost (construction and maintenance) and the hauling cost over the entire life cycle. Ecological issues can be considered as well. The method will be presented and discussed with the help of two case studies. The main benefit of the application of optimization tools consists in an objective-based planning, which allows to check and compare different scenarios and objectives within a short time. The responses coming from the case study regions were highly positive: practitioners suggest to make those methods a standard practice and to further develop the prototype to a user-friendly expert software.

scholarly journals An IoT-Based Smart Home Automation System

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3784
Author(s):  
Cristina Stolojescu-Crisan ◽  
Calin Crisan ◽  
Bogdan-Petru Butunoi
Keyword(s):  
Application Programming Interface ◽  
Smartphone Application ◽  
Raspberry Pi ◽  
Automation System ◽  
Home Automation ◽  
Network Connection ◽  
Communication Scheme ◽  
Application Programming ◽  
Home Automation System ◽  
User Friendly

Home automation has achieved a lot of popularity in recent years, as day-to-day life is getting simpler due to the rapid growth of technology. Almost everything has become digitalized and automatic. In this paper, a system for interconnecting sensors, actuators, and other data sources with the purpose of multiple home automations is proposed. The system is called qToggle and works by leveraging the power of a flexible and powerful Application Programming Interface (API), which represents the foundation of a simple and common communication scheme. The devices used by qToggle are usually sensors or actuators with an upstream network connection implementing the qToggle API. Most devices used by qToggle are based on ESP8266/ESP8285 chips and/or on Raspberry Pi boards. A smartphone application has been developed that allows users to control a series of home appliances and sensors. The qToggle system is user friendly, flexible, and can be further developed by using different devices and add-ons.

scholarly journals Architecture For Automation System Metrics Collection, Visualization and Data Engineering – HAMK Sheet Metal Center Building Automation Case Study

2019 ◽  
Vol 9 (1) ◽  
pp. 561-570
Author(s):  
Khoa Dang ◽  
Igor Trotskii
Keyword(s):  
System Integration ◽  
Data Analytics ◽  
Building Energy ◽  
Facility Management ◽  
Automation System ◽  
Building Energy Efficiency ◽  
Building Automation ◽  
Automation Systems ◽  
Integration Data

AbstractEver growing building energy consumption requires advanced automation and monitoring solutions in order to improve building energy efficiency. Furthermore, aggregation of building automation data, similarly to industrial scenarios allows for condition monitoring and fault diagnostics of the Heating, Ventilations and Air Conditioning (HVAC) system. For existing buildings, the commissioned SCADA solutions provide historical trends, alarms management and setpoint curve adjustments, which are essential features for facility management personnel. The development in Internet of Things (IoT) and Industry 4.0, as well as software microservices enables higher system integration, data analytics and rich visualization to be integrated into the existing infrastructure. This paper presents the implementation of a technology stack, which can be used as a framework for improving existing and new building automation systems by increasing interconnection and integrating data analytics solutions. The implementation solution is realized and evaluated for a nearly zero energy building, as a case study.

scholarly journals How to Use Online Tools to Generate New Hypotheses for Mammary Gland Biology Research: A Case Study for Wnt7b

2021 ◽  
Author(s):  
Yorick Bernardus Cornelis van de Grift ◽  
Nika Heijmans ◽  
Renée van Amerongen
Keyword(s):  
Mammary Gland ◽  
In Silico ◽  
Online Tools ◽  
Mammary Gland Biology ◽  
User Friendly ◽  
In Silico Analyses ◽  
Biology Research ◽  
Selection Of

AbstractAn increasing number of ‘-omics’ datasets, generated by labs all across the world, are becoming available. They contain a wealth of data that are largely unexplored. Not every scientist, however, will have access to the required resources and expertise to analyze such data from scratch. Fortunately, a growing number of investigators is dedicating their time and effort to the development of user friendly, online applications that allow researchers to use and investigate these datasets. Here, we will illustrate the usefulness of such an approach. Using regulation of Wnt7b expression as an example, we will highlight a selection of accessible tools and resources that are available to researchers in the area of mammary gland biology. We show how they can be used for in silico analyses of gene regulatory mechanisms, resulting in new hypotheses and providing leads for experimental follow up. We also call out to the mammary gland community to join forces in a coordinated effort to generate and share additional tissue-specific ‘-omics’ datasets and thereby expand the in silico toolbox.

scholarly journals Predictive Maintenance in Building Facilities: A Machine Learning-Based Approach

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1044
Author(s):  
Yassine Bouabdallaoui ◽  
Zoubeir Lafhaj ◽  
Pascal Yim ◽  
Laure Ducoulombier ◽  
Belkacem Bennadji
Keyword(s):  
Machine Learning ◽  
Model Development ◽  
Predictive Maintenance ◽  
Data Availability ◽  
Machine Learning Techniques ◽  
Automation System ◽  
Building Maintenance ◽  
Collection Data ◽  
Iot Devices

The operation and maintenance of buildings has seen several advances in recent years. Multiple information and communication technology (ICT) solutions have been introduced to better manage building maintenance. However, maintenance practices in buildings remain less efficient and lead to significant energy waste. In this paper, a predictive maintenance framework based on machine learning techniques is proposed. This framework aims to provide guidelines to implement predictive maintenance for building installations. The framework is organised into five steps: data collection, data processing, model development, fault notification and model improvement. A sport facility was selected as a case study in this work to demonstrate the framework. Data were collected from different heating ventilation and air conditioning (HVAC) installations using Internet of Things (IoT) devices and a building automation system (BAS). Then, a deep learning model was used to predict failures. The case study showed the potential of this framework to predict failures. However, multiple obstacles and barriers were observed related to data availability and feedback collection. The overall results of this paper can help to provide guidelines for scientists and practitioners to implement predictive maintenance approaches in buildings.

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