Guy Camilleri

Construction is considered an ecosystem that incorporates many technical, legal, and practical aspects. This article focuses on the practical side of construction, specifically on the use of BIM (building information modeling) during the design phase. In the construction industry, BIM ensures better collaboration and project management by centralizing all information on the same platform. It allows each project stakeholder to exchange documents in real time and contribute to resolving any unforeseen issues or constraints that are encountered. Following an extensive literature review, it has been demonstrated that a lack of communication and collaboration among stakeholders is considered one of the major obstacles to the widespread use of BIM in architectural offices and agencies. The main contribution of this work is to clarify the roles of stakeholders and the rights and temporalities of access, consultation, and modification of the digital BIM model. To achieve this, a collaborative engineering method was applied to propose organizational models for the work of construction stakeholders who are using a collaborative engineering approach during the initial stage of a project (design phase), in order to define the roles of stakeholders and their access to the BIM model.

The drastic growth of electric vehicles and photovoltaics can introduce new challenges, such as electrical current congestion and voltage limit violations due to peak load demands. These issues can be mitigated by controlling the operation of electric vehicles i.e., smart charging. Centralized smart charging solutions have already been proposed in the literature. But such solutions may lack scalability and suffer from inherent drawbacks of centralization, such as a single point of failure, and data privacy concerns. Decentralization can help tackle these challenges. In this paper, a fully decentralized smart charging system is proposed using the philosophy of adaptive multi-agent systems. The proposed system utilizes multi-armed bandit learning to handle uncertainties in the system. The presented system is decentralized, scalable, real-time, model-free, and takes fairness among different players into account. A detailed case study is also presented for performance evaluation.

In the field of microgrids with a significant integration of Renewable Energy Sources, the efficient and practical power storage systems requirement is causing DC microgrids to gain increasing attention. However, uncertainties in power generation and load consumption along with the fluctuations of electricity prices require the design of a reliable control architecture and a robust energy management system for enhancing the power quality and its sustainability, while minimizing the associated costs. This paper presents a mixed approach illustrating both simulation and experimental results of a grid-connected DC microgrid which includes a photovoltaic power source and a battery storage system. Special emphasis is placed on the minimization of the total operating cost of the microgrid while considering the battery degradation cost and the electricity tariff. Thereby, an optimal energy management system is proposed for Energy Storage Systems scheduling and enabling the minimization of the electricity bill based on simple models. Simultaneously, the differences between simulation and laboratory performances are highlighted.

Existing electrical networks are going through a transition and distributed energy resource, if not managed properly, can hinder this transition. Uncontrolled introduction of photovoltaics and electric vehicles in distribution networks would lead to substantial issues such as commitment mismatches, line congestions, voltage deviations, etc. This paper presents the use of a classical approach, mixed integer linear programming optimization, and a novel approach, adaptive multi-agent system, to solve the highlighted distribution side challenges by utilizing electric vehicles' storage capacity. This comparison serves as a great tool to benchmark the performance of the under-development adaptive multi-agent system methodology.

Purpose: This article proposes a strategy to make the testing step easier, generating user acceptance tests (UATs) in an automatic way from requirements artifacts.Design/methodology/approach: This strategy is based on two modeling frameworks: scenarios and task/method paradigm. Scenarios are a requirement artifact used to describe business processes and requirements, and task/method paradigm is a modeling paradigm coming from the artificial intelligence field. The proposed strategy is composed of four steps. In the first step, scenarios are described through a semantic wiki website. Then scenarios are automatically translated into a task/method model (step two). In the third step, the task/method model obtained in step two is executed in order to produce and store all possible achievements of tasks and thus scenarios. The stored achievements are saved in a data structure called execution tree (ET). Finally, from this ET (step four), the UATs are generated.Findings: The feasibility of this strategy is shown through a case study coming from the agriculture production systems field.Originality/value: Generally, test design approaches deal with a small number of variables describing one specific situation where a decision table or workflow is used to design tests. The proposed approach can deal with many variables because the authors rely on scenarios that can be composed in order to obtain a tree with all the testing paths that can arise from their description.

This article focuses on an ontology construction for collaborative decision making. To do this, a state of the art on collaborative decision-making, on ontology engineering and on collaboration engineering has been done. An eight-step ontology development methodology was adopted and implemented to build the ontology. A corpus made up of more than seventy-seven (77) documents was the starting point for the extraction of terms from the ontology and the UML (Unified Modeling Language) language served as a description language of our ontology. This ontology is intended to be the starting point for a facilitation support system in a Collaborative Decision Making process. The aim of the work is to produce a new system according the “Facilitator in the box” paradigm.

Purpose: The design of tests is a very important step in the software development process because it allows us to match the users’ expectations with the finished product. Considered as a cumbersome activity, efforts have been made to automatize and alleviate the burden of test generation, but it is still a largely neglected step. The study aims to propose taking advantage of existing requirement artifacts, like scenarios that describe the dynamic of the domain in a very early stage of software development, to obtain tests from them. Design/methodology/approach: In particular, the approach proposed complement the scenarios that are textually described with a glossary, the language extended lexicon. Thus, a set of rules to derive tests from scenarios is also proposed. The tests are then described using the task/method model. Findings: The main findings of this study consist of an extension of a previously presented set of rules. And, a tool based on a media wiki platform that makes possible to record scenarios and the language extended lexicon and implement the rules to obtain the tests. Originality/value: The main originality of this study is the glossary which complements scenarios, the semantic support to obtain tests and the tool to automatize the approach.