IoT meets distributed AI  Deployment scenarios of Bonseyes AI applications on FIWARE Bonseyes is an Artificial Intelligence (AI) platform composed of a Data Marketplace, a Deep Learning Toolbox, and Developer Reference Platforms with the aim of facilitating tech and nontech companies a rapid adoption of AI as an enabler for their business. Bonseyes provides methods and tools to speed up the development and deployment of AI solutions on low power Internet of Things (IoT) devices, embedded computing systems, and data centre servers. In this work, we address the deployment and the integration of Bonseyes AI applications in a wider enterprise application landscape involving different applications and services. We leverage the wellestablished IoT platform FIWARE to integrate the Bonseyes AI applications into an enterprise ecosystem. This paper presents two AI application deployment and integration scenarios using FIWARE. The first scenario addresses use cases where edge devices have enough compute power to run the AI applications and there is only need to transmit the results to the enterprise ecosystem. The second scenario copes with use cases where an edge device may delegate most of the computation to an externalcloud server. Further, we employ FIWARE IoT Agent generic enabler to manage all edge devices related to Bonseyes AI applications. Both scenarios have been validated on concrete use cases and demonstrators.

An IoT Architecture for Water Resource Management in Agroindustrial Environments: A Case Study in Almerxc3xada (Spain) The current agricultural water panorama in many Mediterranean countries is composed by desalination facilities, wells (frequently overexploited), the water public utility network, and several consumer agents with different water needs. This distributed water network requires centralized management methods for its proper use, which are difficult to implement as the different agents are usually geographically separated. In this sense, the use of enabling technologies such as the Internet of Things can be essential to the proper operation of these agroindustrial systems. In this paper, an Internet of Things cloud architecture based on the FIWARE standard is proposed for interconnecting the several agents that make up the agroindustrial system. In addition, this architecture includes an efficient management method based on a model predictive control technique, which is aimed at minimizing operating costs. A case study inspired by three real facilities located in Almeria (southeast of Spain) is used as the simulation test bed. The obtained results show how around 75% of the total operating costs can be saved with the application of the proposed approach, which could be very significant to decrease the costs of desalinated water and, therefore, to maintain the sustainability of the agricultural system.