Model-Driven Development for Internet of Things: Towards Easing the Concerns of Application Developers

Pal, Arpan; Mukherjee, Arijit; Balamuralidhar, P.

doi:10.1007/978-3-319-19656-5_46

Cited by 11 publications

(4 citation statements)

References 9 publications

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“…Another approach such as [38] proposes a model-driven software development framework that allows users to model IoT environments with several types of devices with many modelling features. It proposes that the stakeholders could add features to the framework.…”

Section: A Limitationsmentioning

confidence: 99%

“…In short, due to the low abstraction layer that this framework provides, the users need to be experts in the IoT and all the concepts around it, such as the hardware used, algorithms or the IoT domain. In [38] an initial prototype had been developed to cover some of the aforementioned aspects. In addition, the IoT applications defined using this framework are deployed using their own implementation.…”

Section: A Limitationsmentioning

confidence: 99%

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SimulateIoT-FIWARE: Domain Specific Language to Design, Code Generation and Execute IoT Simulation Environments on FIWARE

et al. 2022

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Systems based on the Internet of Things (IoT) are continuously growing in many areas such as smart cities, home environments, buildings, agriculture, industry, etc. This system integrates heterogeneous technologies into a complex architecture of interconnected devices capable of communicating, processing, analysing or storing data. There are several IoT platforms that offer several capabilities for the development of these systems. Some of these platforms are Google Cloud's IoT Platform, Microsoft Azure IoT suite, ThingSpeak IoT Platform, Thingworx 8 IoT Platform or FIWARE. However, they are complex IoT platforms where each IoT solution has to be developed ad-hoc and implemented by developers by hand. Consequently, developing IoT solutions is a hard, error-prone and tedious task. Thus, increase the abstraction level from which the IoT systems are designed helps to tackle the underlying technology complexity. In this sense, model-driven development approaches can help to both reduce the IoT application time to market and tackle the technological complexity to develop IoT applications. In this paper, we propose a Domain-Specific Language based on SimulateIoT for the design, code generation and simulation of IoT systems which could be deployed on FIWARE infrastructure (an open-source IoT platform). This implies not only designing the IoT system for a high abstraction level and later on code generation, but also designing and deploying an additional simulation layer to simulate the system on the FIWARE infrastructure before final deployment. The FIWARE IoT environment generated includes the sensors, actuators, fog nodes, cloud nodes and analytical characteristics, which are deployed as microservices on Docker containers and composed suitability to obtain a service-oriented architecture. Finally, two case studies focused on a smart building and an agricultural IoT environment are presented to show the IoT solutions deployed using FIWARE.

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Section: A Limitationsmentioning

confidence: 99%

Section: A Limitationsmentioning

confidence: 99%

SimulateIoT-FIWARE: Domain Specific Language to Design, Code Generation and Execute IoT Simulation Environments on FIWARE

et al. 2022

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“…Instead, a common vocabulary and conceptual model mitigates the effort required for software artefacts to communicate effectively in an energy management system [9], [14]- [17]. Such artefacts are referred to as semantic models, and are being developed using the Web ontology language (OWL), to facilitate the semantic Web [9], [18], [19], Internet of Things [20], and linked data [21]. These ontological semantic models standardize the description of concepts, relationships, and properties in the domain.…”

Section: B Interoperating Legacy Systems With Advanced Analytics-thementioning

confidence: 99%

User Centered Neuro-Fuzzy Energy Management Through Semantic-Based Optimization

Howell

Wicaksono

Yüce

et al. 2019

IEEE Trans. Cybern.

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This paper presents a cloud-based building energy management system, underpinned by semantic middleware, that integrates an enhanced sensor network with advanced analytics, accessible through an intuitive Web-based user interface. The proposed solution is described in terms of its three key layers: 1) user interface; 2) intelligence; and 3) interoperability. The system's intelligence is derived from simulation-based optimized rules, historical sensor data mining, and a fuzzy reasoner. The solution enables interoperability through a semantic knowledge base, which also contributes intelligence through reasoning and inference abilities, and which are enhanced through intelligent rules. Finally, building energy performance monitoring is delivered alongside optimized rule suggestions and a negotiation process in a 3-D Web-based interface using WebGL. The solution has been validated in a real pilot building to illustrate the strength of the approach, where it has shown over 25% energy savings. The relevance of this paper in the field is discussed, and it is argued that the proposed solution is mature enough for testing across further buildings.

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“…There is a few IoT development environments, where algorithm repositories are provided for their exchange in the community, such as in [34] and [35]. This feature should be mandatory in cloud-based IoT development environments, such as Axeda [36], BlueMix [37], and ThingWorx [38].…”

Section: Introductionmentioning

confidence: 99%

MicroServices Suite for Smart City Applications

Badii

Bellini

Difino

et al. 2019

Sensors

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Smart Cities are approaching the Internet of Things (IoT) World. Most of the first-generation Smart City solutions are based on Extract Transform Load (ETL); processes and languages that mainly support pull protocols for data gathering. IoT solutions are moving forward to event-driven processes using push protocols. Thus, the concept of IoT applications has turned out to be widespread; but it was initially “implemented” with ETL; rule-based solutions; and finally; with true data flows. In this paper, these aspects are reviewed, highlighting the requirements for smart city IoT applications and in particular, the ones that implement a set of specific MicroServices for IoT Applications in Smart City contexts. Moreover; our experience has allowed us to implement a suite of MicroServices for Node-RED; which has allowed for the creation of a wide range of new IoT applications for smart cities that includes dashboards, IoT Devices, data analytics, discovery, etc., as well as a corresponding Life Cycle. The proposed solution has been validated against a large number of IoT applications, as it can be verified by accessing the https://www.Snap4City.org portal; while only three of them have been described in the paper. In addition, the reported solution assessment has been carried out by a number of smart city experts. The work has been developed in the framework of the Select4Cities PCP (PreCommercial Procurement), funded by the European Commission as Snap4City platform.

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Model-Driven Development for Internet of Things: Towards Easing the Concerns of Application Developers

Cited by 11 publications

References 9 publications

SimulateIoT-FIWARE: Domain Specific Language to Design, Code Generation and Execute IoT Simulation Environments on FIWARE

SimulateIoT-FIWARE: Domain Specific Language to Design, Code Generation and Execute IoT Simulation Environments on FIWARE

User Centered Neuro-Fuzzy Energy Management Through Semantic-Based Optimization

MicroServices Suite for Smart City Applications

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