Midgar: Creation of a graphic Domain-Specific Language to generate Smart Objects for Internet of Things scenarios using Model-Driven Engineering

• Published in: IEEE access Vol. 8; p. 1
• Main Authors: Garcia, Cristian Gonzalez, Meana-Llorian, Daniel, Garcia-Diaz, Vicente, Jimenez, Andres Camilo, Anzola, John Petearson
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01-01-2020; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Companies; Domain specific languages; Domain-Specific Language; Internet of Things; Model driven engineering; Proposals; Sensors; Smart Objects; Software; Software engineering; Unified modeling language
• DOI: 10.1109/ACCESS.2020.3012503
• EISSN: 2169-3536

Currently, we have around us many Smart Objects. With the use of these objects, we can obtain benefits in our daily lives, as well as recommendations and help when we travel. Alternatively, we may increase and improve our industrial processes through the automation of certain tasks. Notwithstanding, we need to use specific software or to develop our own applications. Nevertheless, the main problem arises when we need to develop our own application because we need to save money, or in other cases, the existing applications are not adapted to us. In this case, it is possible that we need to learn new things, the money will then be spent, and such a process is likely to involve problems related to the Software Crisis. So, the main motivation is to create an environment which can reuse the previous knowledge and help people without knowledge about programming to create Smart Objects. Then, the research question of this paper is the following: Could we enable the creation of Smart Objects in an easy and efficient way for people who do not have programming skills? As a possible solution, we have developed a graphic Domain-Specific Language using the Midgar platform. In order to validate our proposal, we make an evaluation split into different phases; the first one consisted in measuring data obtained from participants when they were performing a specific task, and the second one consisted of a survey to collect their opinions about our proposal. Moreover, we also did a comparison of the measured data between two graphical editors and two different participant profiles according to their knowledge about Smart Objects.