it could rain weather forecasting as a reasoning process

Abstract Meteorological forecasting is the process of providing reliable prediction about the future weathear within a given interval of time. Forecasters adopt a model of reasoning that can be mapped onto an integrated conceptual framework. A forecaster essentially precesses data in advance by using some models of machine learning to extract macroscopic tendencies such as air movements, pressure, temperature, and humidity differentials measured in ways that depend upon the model, but fundamentally, as gradients. Limit values are employed to transform these tendencies in fuzzy values, and then compared to each other in order to extract indicators, and then evaluate these indicators by means of priorities based upon distance in fuzzy values. We formalise the method proposed above in a workflow of evaluation steps, and propose an architecture that implements the reasoning techniques

onto plc an ontology driven methodology for converting plc industrial plants to iot

Abstract We present the new methodology ONTO-PLC to deliver software programs on system-on-chip or single-board computers used to control industrial plants, as substitutes for programmable logic control technologies. The methodology is ontology-driven based on the abstract description of the plant at a level in which the plant itself is viewed as a set of instruments, each instrument being a set of machineries coordinated in functional terms by a control system, formed by sensors and actuators, under the control of an abstract model of behavior delivered by means of an extended finite state machine

Applications of Linear Defeasible Logic: combining resource consumption and exceptions to energy management and business processes

Linear Logic and Defeasible Logic have been adopted to formalise different features of knowledge representation: consumption of resources, and non monotonic reasoning in particular to represent exceptions. Recently, a framework to combine sub-structural features, corresponding to the consumption of resources, with defeasibility aspects to handle potentially conflicting information, has been discussed in literature, by some of the authors. Two applications emerged that are very relevant: energy management and business process management. We illustrate a set of guide lines to determine how to apply linear defeasible logic to those contexts.Comment: In Proceedings DICE-FOPARA 2019, arXiv:1908.04478. arXiv admin note: substantial text overlap with arXiv:1809.0365

Protecting the environment: A multi-agent approach to environmental monitoring

In this paper we discuss a transition model from commonly adopted models of data gathering, transfer and management for environmental monitoring towards more sophisticated ones based on Artificial Intelligence and IoT. The transition model is based on the paradigm of multiple agent systems. The adoption of this transition model is motivated by the need to improve effectiveness, efficiency and interoperability of environmental monitoring by simultaneously guaranteeing its sustainability in economic term

Innovation for the digitization process of the AECO sector

In this article I will develop the following points: 1. The imagination is structurally technological as it is entangled with historically dominant technologies; 2. These orientate the reconfiguration of its multimodality, i.e. the fact that the imagination does not work only on the optical and visual level but extends its action to all of our sensorimotor system; 3. How this re-modeling is influenced by digital technologies remains to be clarified; 4. In this problematic field there are two opposing lines of development, which I will treat with some examples

Cyber-Physical Systems Improving Building Energy Management: Digital Twin and Artificial Intelligence

The research explores the potential of digital-twin-based methods and approaches aimed at achieving an intelligent optimization and automation system for energy management of a residential district through the use of three-dimensional data model integrated with Internet of Things, artificial intelligence and machine learning. The case study is focused on Rinascimento III in Rome, an area consisting of 16 eight-floor buildings with 216 apartment units powered by 70% of self-renewable energy. The combined use of integrated dynamic analysis algorithms has allowed the evaluation of different scenarios of energy efficiency intervention aimed at achieving a virtuous energy management of the complex, keeping the actual internal comfort and climate conditions. Meanwhile, the objective is also to plan and deploy a cost-effective IT (information technology) infrastructure able to provide reliable data using edge-computing paradigm. Therefore, the developed methodology led to the evaluation of the effectiveness and efficiency of integrative systems for renewable energy production from solar energy necessary to raise the threshold of self-produced energy, meeting the nZEB (near zero energy buildings) requirements

Open Data and Models for Energy and Environment

This Special Issue aims at providing recent advancements on open data and models. Energy and environment are the fields of application.For all the aforementioned reasons, we encourage researchers and professionals to share their original works. Topics of primary interest include, but are not limited to:Open data and models for energy sustainability;Open data science and environment applications;Open science and open governance for Sustainable Development Goals;Key performance indicators of data-aware energy modelling, planning and policy;Energy, water and sustainability database for building, district and regional systems; andBest practices and case studies

Defeasible Reasoning about Electric Consumptions

Conflicting rules and rules with exceptions are very common in natural language specification of behaviour of devices in real-world context. This is common exactly because those specifications are processed by humans, and humans apply common sense, and strategic reasoning about those rules. In this paper we deal with the challenge of providing, step by step, a model of energy saving rule specification and processing methods that are to be used to reduce the consumptions of a system of devices, and appear conflictual and typical (not universal). We argue that a very good nonmonotonical approach to such a problem can lie upon defeasible logic. We provide a formalism, that, starting with rules specified at an abstract level, but compatibly with natural aspects of this specification, including temporal constraints, and power absorption ones, generates the extension of a basic defeasible logic, that correspond to turned on or off devices