{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,28]],"date-time":"2026-04-28T12:55:46Z","timestamp":1777380946098,"version":"3.51.4"},"reference-count":114,"publisher":"SAGE Publications","issue":"1","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["AIS"],"published-print":{"date-parts":[[2024,3,14]]},"abstract":"<jats:p>Since its introduction by Mark Weiser, ubiquitous computing has received increased interest in the dawn of technological advancement. Supported by wireless technology advancement, embedded systems, miniaturization, and the integration of various intelligent and communicative devise, context-aware ubiquitous applications actively and intelligently use rich contextual information to assist their users. However, their designs are subject to continuous changes imposed by external factors. Nowadays, software engineering, particularly in the fields of Model-Driven Engineering, displays a strong tendency towards developing applications for pervasive computing. This trend is also fueled by the rise of generative artificial intelligence, paving the way for a new generation of no-code development tools and models specifically trained on open-source code repositories to generate applications from their descriptions. The specificities of our approach lies in starting with a graphical model expressed using a domain-specific language (DSL) composed of symbols and formal notations. This allows for graphically instantiating and editing applications, guiding and assisting experts from various engineering fields in defining ubiquitous applications that are eventually transformed into peculiar models. We believe that creating intelligent models is the best way to promote software development efficiency. We have used and evaluated recurrent neural networks, leveraging the recurrence of processing the same contextual information collected within this model, and enabling iterative adaptation to future evolutions in ubiquitous systems. We propose a prototype instantiated by our meta-model which tracks the movements of individuals who were positive for COVID-19 and confirmed to be contagious. Different deep learning models and classical machine learning techniques are considered and compared for the task of detection\/classification of COVID-19. Results obtained from all techniques were evaluated with confusion matrices, accuracy, precision, recall and F1-score. In summary, most of the results are very impressive. Our deep learning approach used a RNN architecture produced up to 92.1% accuracy. With the recent development of OpenAI Codex, optimized for programming languages, we provided the same requirements to the Codex model and asked it to generate the source code for the COVID-19 application, comparing it with the application generated by our workshop.<\/jats:p>","DOI":"10.3233\/ais-220355","type":"journal-article","created":{"date-parts":[[2023,12,12]],"date-time":"2023-12-12T11:25:24Z","timestamp":1702380324000},"page":"111-149","source":"Crossref","is-referenced-by-count":3,"title":["From programming-to-modeling-to-prompts smart ubiquitous applications"],"prefix":"10.1177","volume":"16","author":[{"given":"Mohammed Fethi","family":"Khalfi","sequence":"first","affiliation":[{"name":"LabRI-SBA Lab (ESI-SBA), Department of Computer Science, University of Djillali Liabes, Sidi Bel-Abbes, Algeria"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mohammed Nadjib","family":"Tabbiche","sequence":"additional","affiliation":[{"name":"EEDIS Lab, Department of Computer Science, University of Djillali Liabes, Sidi Bel-Abbes, Algeria"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Reda","family":"Adjoudj","sequence":"additional","affiliation":[{"name":"EEDIS Lab, Department of Computer Science, University of Djillali Liabes, Sidi Bel-Abbes, Algeria"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","reference":[{"key":"10.3233\/AIS-220355_ref1","doi-asserted-by":"publisher","DOI":"10.1007\/s13278-023-01077-w"},{"key":"10.3233\/AIS-220355_ref2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-27997-3_20"},{"key":"10.3233\/AIS-220355_ref3","doi-asserted-by":"crossref","unstructured":"A.\u00a0Achilleos, K.\u00a0Yang and N.\u00a0Georgalas, Context modelling and a context-aware framework for pervasive service creation: A model-driven approach, in: Pervasive and Mobile Computing, Vol.\u00a06, 2010, pp.\u00a0281\u2013296.","DOI":"10.1016\/j.pmcj.2009.07.014"},{"key":"10.3233\/AIS-220355_ref4","doi-asserted-by":"publisher","DOI":"10.1007\/s10664-023-10312-z"},{"key":"10.3233\/AIS-220355_ref6","doi-asserted-by":"publisher","DOI":"10.1007\/11773887_17"},{"key":"10.3233\/AIS-220355_ref7","doi-asserted-by":"crossref","unstructured":"A.\u00a0Alti and A.\u00a0Boukerram, Enabling self-management in context-aware quality model driven approach, in: 10th International Symposium on Programming and Systems, 2011, pp.\u00a075\u201383.","DOI":"10.1109\/ISPS.2011.5898866"},{"key":"10.3233\/AIS-220355_ref8","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-022-05052-x"},{"key":"10.3233\/AIS-220355_ref9","doi-asserted-by":"publisher","DOI":"10.1007\/s10462-023-10419-1"},{"key":"10.3233\/AIS-220355_ref10","doi-asserted-by":"publisher","first-page":"481","DOI":"10.1007\/s10270-013-0344-6","article-title":"Model-driven engineering of middleware-based ubiquitous services","volume":"13","author":"Autili","year":"2014","journal-title":"Softw Syst Model"},{"key":"10.3233\/AIS-220355_ref11","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.rinp.2021.104495","article-title":"Time series forecasting of new cases and new deaths rate for Covid-19 using deep learning methods","volume":"27","author":"Ayoobi","year":"2021","journal-title":"Results Phys"},{"key":"10.3233\/AIS-220355_ref12","doi-asserted-by":"crossref","first-page":"116056","DOI":"10.1109\/ACCESS.2019.2931001","article-title":"CIM-CSS: A formal modeling approach to context identification and management for intelligent context- sensitive systems","volume":"7","author":"Baddour","year":"2019","journal-title":"IEEE Access"},{"key":"10.3233\/AIS-220355_ref13","doi-asserted-by":"publisher","DOI":"10.1109\/ICMCS.2012.6320249"},{"key":"10.3233\/AIS-220355_ref14","doi-asserted-by":"crossref","unstructured":"F.\u00a0Bedini, R.\u00a0Maschotta and A.\u00a0Zimmermann, A generative approach for creating eclipse Sirius editors for generic systems, in: IEEE International Systems Conference (SysCon), 2021, pp.\u00a01\u20138.","DOI":"10.1109\/SysCon48628.2021.9447062"},{"key":"10.3233\/AIS-220355_ref15","doi-asserted-by":"publisher","first-page":"293","DOI":"10.1007\/s12193-018-0277-z","article-title":"Model driven approach for adapting user interfaces to the context of accessibility: Case of visually impaired users","volume":"13","author":"Bendaly Hlaoui","year":"2019","journal-title":"J Multimodal User Interfaces"},{"key":"10.3233\/AIS-220355_ref16","doi-asserted-by":"publisher","first-page":"375","DOI":"10.1007\/s12243-019-00709-7","article-title":"Access control in the Internet of things: A survey of existing approaches and open research questions","volume":"74","author":"Bertin","year":"2019","journal-title":"Ann. 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