## 5 Conclusions  
The Internet of Things will become a reality when connected object makers propose off-the-shelf cyber-physical objects that can communicate and interoperate through open standard protocols and data formats, or that can be connected to Web of Things (WoT) platforms that bridge the gap between proprietary protocols and Web standard formats and protocols. Such objects and platforms appear as attractive solutions to build complex systems, notably for environmental sensing and for smart agriculture and farming. Nevertheless, in challenging environments, such as in agricultural and farming environments, it is often difficult to deploy systems relying exclusively on infrastructure-based networks because rural areas often have poor network coverage, and because there are frequent and unpredictable connectivity disruptions resulting from both the mobility of agricultural machines (e.g., tractors, agribots, and drones) communicating with short range radio interfaces and from the sleep phases kept by some devices for energy saving purposes.  
In this paper, we present how opportunistic computing can be combined with the WoT to contribute to the smart agriculture, and how such an approach was implemented in a middleware platform called ASAWoO. Opportunistic computing and networking techniques leverage the mobility of agricultural machines to provide intermittent connectivity between physical objects that would not have been connected by any route otherwise. This platform provides a virtual representation of the physical objects in the Web, called Avatars, which give access to the objects functionalities in order to allow WoT users to interact with devices at a higher level of abstraction.  
ASAWoO platform was evaluated in a practical smart agriculture scenario through a four-month experiment. Two tractors carried ASAWoO instances responsible for collecting data of sensors disseminated in an experimental farm. Experiment results show that ASAWoO platform was able to perform environmental sensing using opportunistic computing in real conditions, and that the low pace of farming vehicles makes opportunistic computing possible in the agricultural context. Based on these outcomes, we conclude that both the integration of sensors and actuators such as agribotsin WoT applications, and the implementation of opportunistic computing mechanisms are likely to improve agricultural practices and compensate for the potential lack of network infrastructure. Such an approach is not limited to smart agriculture and farming, and could also be transposed to other related critical contexts such as disaster relief.  
Data curation, N.L.S.; Investigation, L.T.; Resources, N.L.S.; Software, L.T. and N.L.S.; Supervision, N.L.S.; Validation, L.T.; Visualization, L.T.; Writing--original draft, L.T. and N.L.S.; and Writing--review and editing, L.T. and N.L.S.  
This work was supported by the French ANR (Agence Nationale de la Recherche) grant number ANR-13-INFR-012.  
The experiment presented in this article would not have been possible without the helpful support provided by IRESTA from Montoldre and Clermont-Ferrand. We would also like to thank other partners for their valuable contributions to the ASAwoO project: TWEAK team from Lyon 1 university LIRIS lab ([[http://liris.cnrs.fr/](http://liris.cnrs.fr/)]([http://liris.cnrs.fr/](http://liris.cnrs.fr/))), COSY team from Valence-Grenoble LCIS lab ([[http://lcis.grenoble-inp.fr/](http://lcis.grenoble-inp.fr/)]([http://lcis.grenoble-inp.fr/](http://lcis.grenoble-inp.fr/))), and Generation Robots ([[https://generationrobots.com/](https://generationrobots.com/)]([https://generationrobots.com/](https://generationrobots.com/))).  
The authors declare no conflict of interest.