Semantic IoT Middleware-enabled Mobile Complex Event Processing for Integrated Pest Management

Francesco Nocera, Tommaso di Noia, Marina Mongiello, Eugenio Di Sciascio

2017

Abstract

Agricultural domain presents challenges typical of the Cyber-Physical Systems field and the hard-core of information technology industry of the new generation, such as Cloud computing and Internet of Things. In fact, modern agricultural management strongly relies on many different sensing methodologies to provide accurate information about crop, climate, and environmental conditions. In this paper we propose an approach to model a mobile-driven and distributed Complex Event Processing solution which is enabled by an IoT middleware. The proposed framework is robust with reference to contextual and environmental changes also thanks to the exploitation of an ontological model.

Paper Citation

in Harvard Style

Nocera F., di Noia T., Mongiello M. and Di Sciascio E. (2017). Semantic IoT Middleware-enabled Mobile Complex Event Processing for Integrated Pest Management . In Proceedings of the 7th International Conference on Cloud Computing and Services Science - Volume 1: CLOSER, ISBN 978-989-758-243-1, pages 638-645. DOI: 10.5220/0006369506380645

in Bibtex Style

@conference{closer17,
author={Francesco Nocera and Tommaso di Noia and Marina Mongiello and Eugenio Di Sciascio},
title={Semantic IoT Middleware-enabled Mobile Complex Event Processing for Integrated Pest Management},
booktitle={Proceedings of the 7th International Conference on Cloud Computing and Services Science - Volume 1: CLOSER,},
year={2017},
pages={638-645},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006369506380645},
isbn={978-989-758-243-1},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 7th International Conference on Cloud Computing and Services Science - Volume 1: CLOSER,
TI - Semantic IoT Middleware-enabled Mobile Complex Event Processing for Integrated Pest Management
SN - 978-989-758-243-1
AU - Nocera F.
AU - di Noia T.
AU - Mongiello M.
AU - Di Sciascio E.
PY - 2017
SP - 638
EP - 645
DO - 10.5220/0006369506380645