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Farming is facing many economic challenges in terms of productivity and cost-effectiveness. Labor shortage partly due to depopulation of rural areas, especially in Europe, is another challenge. Domain specific problems such as accurate monitoring of soil and crop properties and animal health are key factors for minimizing economical risks, and not risking human health. The ECSEL AFarCloud (Aggregate Farming in the Cloud) project will provide a distributed platform for autonomous farming that will allow the integration and cooperation of agriculture Cyber Physical Systems in real-time in order to increase efficiency, productivity, animal health, food quality and reduce farm labor costs. Moreover, such a platform can be integrated with farm management software to support monitoring and decision-making solutions based on big data and real-time data mining techniques. A special thanks to all the AFarCloud consortium people that have worked on the AFarCloud proposal on which this paper is based on. The AFarCloud project is funded from the ECSEL Joint Undertaking under grant agreement n◦783221, and from several National funding agencies. It is worth noting some ECSEL projects that have provided background and/or reusable results taken into account in AFarCloud: MegaM@rt2 [34], SafeCOP [35], and AQUAS [36].

Background Traffic-related air pollution is a potential risk factor for human respiratory health. A Geographical Information System (GIS) approach was used to examine whether distance from a main road (the Tosco-Romagnola road) affected respiratory health status. Methods We used data collected during an epidemiological survey performed in the Pisa-Cascina area (central Italy) in the period 1991-93. A total of 2841 subjects participated in the survey and filled out a standardized questionnaire on health status, socio-demographic information, and personal habits. A variable proportion of subjects performed lung function and allergy tests. Highly exposed subjects were defined as those living within 100 m of the main road, moderately exposed as those living between 100 and 250 m from the road, and unexposed as those living between 250 and 800 m from the road. Statistical analyses were conducted to compare the risks for respiratory symptoms and diseases between exposed and unexposed. All analyses were stratified by gender. Results The study comprised 2062 subjects: mean age was 45.9 years for men and 48.9 years for women. Compared to subjects living between 250 m and 800 m from the main road, subjects living within 100 m of the main road had increased adjusted risks for persistent wheeze (OR = 1.76, 95% CI = 1.08-2.87), COPD diagnosis (OR = 1.80, 95% CI = 1.03-3.08), and reduced FEV1/FVC ratio (OR = 2.07, 95% CI = 1.11-3.87) among males, and for dyspnea (OR = 1.61, 95% CI = 1.13-2.27), positivity to skin prick test (OR = 1.83, 95% CI = 1.11-3.00), asthma diagnosis (OR = 1.68, 95% CI = 0.97-2.88) and attacks of shortness of breath with wheeze (OR = 1.67, 95% CI = 0.98-2.84) among females. Conclusion This study points out the potential effects of traffic-related air pollution on respiratory health status, including lung function impairment. It also highlights the added value of GIS in environmental health research.

DomoML is a mark-up language aimed at the definition of interoperability standard for domestic resources within the NICHE project (Natural Interaction in Computerised Home Environment). The project focuses on human language as a means for mediating user interaction with the home environment, enabling a user to control, query and program devices. Various heterogeneous components are going to take part in this architecture, and DomoML is the glue which allows them to be interfaced. It is a mark-up language intended to define a semantic layer on which novel value-added services (agents) can easily be built.