Finding new ways to manage the increased data usage and to improve the level of service required by the new wave of smartphones applications is an essential issue. MACACO project proposes an innovative solution to this problem by focusing on data offloading mechanisms that take advantage of context and content information. Our intuition is that if it is possible to extract and forecast the behaviour of mobile network users in the three-dimensional space of time, location and interest (i.e. ‘what data’, ‘when’ and ‘where’ users are pulling data from the network), it is possible to derive efficient data offloading protocols. Such protocols would pre-fetch the identified data and cache it at the network edge at an earlier time, preferably when the mobile network is less charged, or offers better quality of service. Caching can be done directly at the mobile terminals, but as well at the edge nodes of the network (e.g., femtocells or wireless access points). Building on previous research efforts in the fields of social wireless networking, opportunistic communications and content networking, MACACO will address several issues. The first one is to derive appropriate models for the correlation between user interests and their mobility. Lots of studies have characterized mobile nodes mobility based on real world data traces, but knowledge about the interactions with user interests in this context is still missing. To fill this gap, MACACO proposes to acquire real world data sets to model mobile node behaviour in the aforementioned three-dimensional space. The second issue addressed is the derivation of efficient data-offloading algorithms leveraging the large-scale data traces and corresponding models. Firstly, simple and efficient prediction algorithms will be derived to forecast the node’s mobility and interests. Then, MACACO has to output data pre-fetching mechanisms that both improves the perceived quality of service of the mobile user and noticeably offloads pick bandwidth demands at the cellular network. A proof of concept will be exhibited though a federated testbed located in France, Switzerland and in the UK. The consortium was carefully constituted to gather partners that are pretty complementary and qualified to address the context-content correlation and related data offloading challenge. The partners of MACACO will combine research and experience in a wide set of areas to gain unique competence, which will be brought forward to other European partners through the dissemination and exploitation activities of the consortium.

Water transport and distribution systems must be carefully monitored and operated to avoid water losses, to safe energy and to protect the assets of the water utilities against damages. In major water transport and distribution systems this task is performed by centralized SCADA (Supervisory Control and Data Acquisition) systems which receive information from remote sensors and remotely control components like valves and pumps. SCADA systems are technically complex and expensive. For this reason, they often are not achievable for small water utilities which do have to operate their transport lines and distribution networks manually. Recent developments in ICT (Information and Communications Technology) open new paths for technologically advanced, low-cost solutions for water system monitoring and control. In the first place it is the decentralized IoT (Internet of Things) approach which already gained significant importance in the industrial sector but is still in an embryonal stage considering water utilities. To explore the promising potential of IoT technologies in combination with other innovative ICT the IoT.WATER project sets up an interdisciplinary consortium, bringing together the expertise needed for this task: •The Institute of Fluid Mechanics and Turbomachinery of the Technical University of Kaiserslautern, Germany (SAM) is specialized in optimization of machine design, condition monitoring and decision support for optimized operation of hydraulic and thermal turbomachinery. SAM will act as project coordinator. •The Centro de Pesquisas Hidráulicas e Recursos Hídricos of the Federal University of Minas Gerais, Brazil (CPH) is a hydraulic research center dedicated to support the energy and water supply sectors, with a team of professors on the fields of civil, mechanical, electrical and automation engineering. •The research group HECE of Liege University conducts experimental and numerical research in hydraulic engineering. The group has been developing the modelling system WOLF, which enables the computation of pressurized, free surface and mixed flow in channel and pipe networks. The flow models are coupled to self-developed optimization algorithms. WOLF is routinely used for teaching, research and consultancy. •The MIND research group from INSA Rouen Normandie, France (MIND) conducting research in the fields of Multi-Agent Systems, Semantic Technologies and Human-Machine Interactions. Focus is the study and development of interaction and decision-making processes in mixed communities or in cyber-physical systems. •The Dr. Kraetzig Ingenieurgesellschaft mbH, Aachen, Germany (KI) as a SME engineering company with expertise in setting up distributed monitoring and control networks for environmental control, water system optimization and water loss reduction. The project proposal follows a systematic approach starting with high time resolution measurements in water systems (already based on IoT technology), numerical description and characterization of the water systems, adaptation and development of hydraulic models suitable for near-real-time simulation, development of tools for implementation in IoT nodes for optimizing of component operation (e.g. pump operation / condition monitoring) and for supporting decision making (e.g. energy efficient management, alarm generation in case of incidents etc.), testing and system comparison by use of “water system digital twins” and physical water system models. The overall IoT system will be installed in systems in Belgium, Brazil and Germany for extended field testing. Further application in other water utilities will be supported by documentation of the used methodology. The outcome of the project will be a new ICT approach for low-cost water system monitoring and operation. This system will contribute to water loss reduction, backing the efforts against impacts of water scarcity, simpler maintenance strategies and strengthening of water systems resilience against havocs.