Izvorni znanstveni članak
https://doi.org/10.24138/jcomss.v14i1.438
Top-Down Delivery of IoT-based Applications for Seniors Behavior Change Capturing Exploiting a Model-Driven Approach
Alessandro Fiore
; University of Salento, Italy
Adriana Caione
; University of Salento, Italy
Luca Mainetti
; University of Salento, Italy
Luigi Manco
; University of Salento, Italy
Roberto Vergallo
; University of Salento, Italy
Sažetak
Developing Internet of Things (IoT) requires expertise and considerable skills in different fields in order to cover all the involved heterogeneous technologies, communication formats and protocols. Developers and experts ask for new solutions that speed up the prototyping of IoT applications. One of these solutions is Web of Topics (WoX) middleware, a model-driven Cloud platform that aims to ease IoT applications developing, introducing a strong semantic abstraction of the IoT concepts. In WoX, almost all the IoT entities and concepts are limited to the concept of Topic, i.e. an entity containing the value of a feature of interest that we intend to detect. The local counterpart of WoX is L-WoX (Local-Web of Topics), which manages local instances of features of interest, allowing mobile applications to collaborate among them, offering and receiving data to/from smart objects, and enabling the communication with WoX Cloud platform. The presented study leverages WoX approach for showing an experience in rapid design and prototyping of an ambient assisted living system that detects the movements of elderly persons in their home, acquiring data through sensors in an unobtrusive way. Moreover, The paper shows that the chosen model-driven solution is very suitable in a top-down approach, starting from users requirements: the created system simplifies the user-centered design of IoT applications, adopting a full top-down approach from user required to the technological solution.
Ključne riječi
IoT; WoX; middleware; smart environment; behavior analysis
Hrčak ID:
199203
URI
Datum izdavanja:
15.3.2018.
Posjeta: 823 *