Intelligent Energy Management with IoT Framework in Smart Cities Using Intelligent Analysis: An Application of Machine Learning Methods for Complex Networks and Systems

Smart buildings are increasingly using Internet of Things (IoT)-based wireless sensing systems to reduce their energy consumption and environmental impact. As a result of their compact size and ability to sense, measure, and compute all electrical properties, Internet of Things devices have become increasingly important in our society. A major contribution of this study is the development of a comprehensive IoT-based framework for smart city energy management, incorporating multiple components of IoT architecture and framework. An IoT framework for intelligent energy management applications that employ intelligent analysis is an essential system component that collects and stores information. Additionally, it serves as a platform for the development of applications by other companies. Furthermore, we have studied intelligent energy management solutions based on intelligent mechanisms. The depletion of energy resources and the increase in energy demand have led to an increase in energy consumption and building maintenance. The data collected is used to monitor, control, and enhance the efficiency of the system

Smart Buildings

This talk presents an efficient cyberphysical platform for the smart management of smart buildings http://www.deepint.net. It is efficient because it facilitates the implementation of data acquisition and data management methods, as well as data representation and dashboard configuration. The platform allows for the use of any type of data source, ranging from the measurements of a multi-functional IoT sensing devices to relational and non-relational databases. It is also smart because it incorporates a complete artificial intelligence suit for data analysis; it includes techniques for data classification, clustering, forecasting, optimization, visualization, etc. It is also compatible with the edge computing concept, allowing for the distribution of intelligence and the use of intelligent sensors. The concept of smart building is evolving and adapting to new applications; the trend to create intelligent neighbourhoods, districts or territories is becoming increasingly popular, as opposed to the previous approach of managing an entire megacity. In this paper, the platform is presented, and its architecture and functionalities are described. Moreover, its operation has been validated in a case study at Salamanca - Ecocasa. This platform could enable smart building to develop adapted knowledge management systems, adapt them to new requirements and to use multiple types of data, and execute efficient computational and artificial intelligence algorithms. The platform optimizes the decisions taken by human experts through explainable artificial intelligence models that obtain data from IoT sensors, databases, the Internet, etc. The global intelligence of the platform could potentially coordinate its decision-making processes with intelligent nodes installed in the edge, which would use the most advanced data processing techniques

Research on the Development Status and the Trend of Smart Home

The emergence of the Internet of Things (IoT) technology provides new directions and contents for the development of smart homes, breaks the time and space barriers between people and home systems, and the application of IoT technology realizes the integration and management of information between smart home devices, prompting people\u27s home life to be safe, comfortable and intelligent, exploring the life needs of contemporary users, and building a harmonious relationship between people and smart home systems. At present, smart home is developing rapidly and has a greater impact on people\u27s home life. This paper will elaborate on the development status of smart homes in the context of the Internet of Things and explore and study the significance and development trend of Internet of Things technology in the field of the smart home

Dynamic Energy Management Method with Demand Response Interaction Applied in an Office Building

The intelligent management systems of the end consumers are endowed with advanced functions being one of them the interaction with external entities through the automatic participation in demand response programs. The development of the intelligent management systems is to reduce the energy consumption based on internal information and on the interaction with an external entity. Moreover, the management approaches results in an active participation of the consumers in the operation of the smart grids and microgrids concepts. The paper developed presents the application of a dynamic priority method in SCADA Office Intelligent Context Awareness Management system to manage the energy resources installed in an office building. The intelligent management method allows the dynamic active participation of the office building in the DR events considering the real data of consumption and generation of one building in Polytechnic of Porto. The main goal of the methodology is to obtain a dynamic scheduling for all energy resources with little interference in the comfort of users. The results of dynamic management model in office building are discussed for the participation in 8 hours demand response event. The power limit of the scenario depends on the consumption and micro-generation power of an October day.The present work was done and funded in the scope of the following projects: H2020 DREAM-GO Project (Marie Sklodowska-Curie grant agreement No 641794); EUREKA - ITEA2 Project SEAS with project number 12004; AVIGAE Project (P2020 - 3401); UID/EEA/00760/2013 funded by FEDER Funds through COMPETE program and by National Funds through FCT, and GECAD–EEA/00760.info:eu-repo/semantics/publishedVersio

Integrating building and urban semantics to empower smart water solutions

Current urban water research involves intelligent sensing, systems integration, proactive users and data-driven management through advanced analytics. The convergence of building information modeling with the smart water field provides an opportunity to transcend existing operational barriers. Such research would pave the way for demand-side management, active consumers, and demand-optimized networks, through interoperability and a system of systems approach. This paper presents a semantic knowledge management service and domain ontology which support a novel cloud-edge solution, by unifying domestic socio-technical water systems with clean and waste networks at an urban scale, to deliver value-added services for consumers and network operators. The web service integrates state of the art sensing, data analytics and middleware components. We propose an ontology for the domain which describes smart homes, smart metering, telemetry, and geographic information systems, alongside social concepts. This integrates previously isolated systems as well as supply and demand-side interventions, to improve system performance. A use case of demand-optimized management is introduced, and smart home application interoperability is demonstrated, before the performance of the semantic web service is presented and compared to alternatives. Our findings suggest that semantic web technologies and IoT can merge to bring together large data models with dynamic data streams, to support powerful applications in the operational phase of built environment systems

Development of mobile indoor positioning system application using android and bluetooth low energy with trilateration method

This proceedings volume contains papers presented at the fifth International Conference on Soft Computing, Intelligent System and Information Technology (the 5th ICSIIT) held in Bali, Indonesia, 26-29 September 2017. Main theme of this international conference is �Building Intelligence through IoT and Big Data�, and it was organized and hosted by Informatics Engineering Department, Petra Christian University, Surabaya, Indonesia. The Program Committee received 106 submissions for the conference from across Indonesia and around the world. After peer-review process by at least two reviewers per paper, 64 papers were accepted and included in the proceedings. The papers were divided into ten groups: Classification and Correlation Techniques, Feature Extraction and Image Recognition Methods, Algorithms for Intelligent Computation, Distributed Systems and Computer Networks, Mobile and Pervasive IoT Applications, Assessments of Integrated IS/IT, Simulation and Virtual Reality Applications, Smart Assistive Technologies, Smart Mobile Applications, Case Studies of Knowledge Discovery and Management

Development of Interactive Learning Media for Simulating Human Blood Circulatory System

This proceedings volume contains papers presented at the fifth International Conference on Soft Computing, Intelligent System and Information Technology (the 5th ICSIIT) held in Bali, Indonesia, 26-29 September 2017. Main theme of this international conference is “Building Intelligence through IoT and Big Data”, and it was organized and hosted by Informatics Engineering Department, Petra Christian University, Surabaya, Indonesia. The Program Committee received 106 submissions for the conference from across Indonesia and around the world. After peer-review process by at least two reviewers per paper, 64 papers were accepted and included in the proceedings. The papers were divided into ten groups: Classification and Correlation Techniques, Feature Extraction and Image Recognition Methods, Algorithms for Intelligent Computation, Distributed Systems and Computer Networks, Mobile and Pervasive IoT Applications, Assessments of Integrated IS/IT, Simulation and Virtual Reality Applications, Smart Assistive Technologies, Smart Mobile Applications, Case Studies of Knowledge Discovery and Management

Intelligent HVAC systems for smart modern building

The modern smart building offers software solution and sensing the surrounding environment. However, this will be allowed management easily for leaders that are providing better control and optimize heating, ventilation, and air conditioning (HVAC)، as well as this is consider from the important topics in mechanical engineering modern application. In this paper, a new intelligent HVAC system is proposed for modern smart building. The proposed system is heavily based on one of the most efficient tools of artificial intelligence which is a support vector machine. This technique will be depended on the data set to detect the HVAC system for any building. In this case, it will save time as well as it has the ability to provide a suitable system without any delay. The HVAC system that proposed in this paper is very important issues in design modern building. According to for training and testing phases for the proposed system, we can easily notice efficiency and effectiveness for the cooling and heating systems