Food industry is the production sector with the highest energy consumption. In Europe, the energy used to produce food accounts for 26% of total energy consumption. Over 28% is used in industrial processes. Recently, European food companies have increased their efforts to make their production processes more sustainable, also by giving preference to the use of renewable energy sources. In Italy, the total energy consumption in agriculture and food sectors decreased between 2013 and 2014, passing from 16.79 to 13.3 Mtep. Since energy consumption in food industry is nearly twice the one in agriculture (8.57 and 4.73 Mtep, respectively), it is very important to improve energy efficiency and use green technologies in all the phases of food processing and conservation. In Italy, a recent law (Legislative Decree 102, 04/07/2014) has made energy-use diagnosis compulsory for all industrial concerns, particularly for those showing high consumption levels. In the case of food industry buildings, energy is mainly used for indoor microclimate control, which is needed to ensure workers' wellbeing and the most favourable conditions for food processing and conservation. To this end, it is important to have tools and methods allowing for easy, rapid and precise energy performance assessment of agri-food buildings. The accuracy of the results obtainable from the currently available computational models depends on the grade of detail and information used in constructional and geometric modelling. Moreover, this phase is probably the most critical and time-consuming in the energy diagnosis. In this context, fine surveying and advanced 3D geometric modelling procedures can facilitate building modelling and allow technicians and professionals in the agri-food sector to use highly efficient and accurate energy analysis and evaluation models. This paper proposes a dedicated model for energy performance assessment in agri-food buildings. It also shows that by using advanced surveying techniques, such as a terrestrial laser scanner and an infrared camera, it is possible to create a three-dimensional parametric model, while, thanks to the heat flow meter measurement method, it is also possible to obtain a thermophysical model. This model allows assessing the energy performance of agri-food buildings in order to improve the indoor microclimate control and the conditions of food processing and conservation.

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In Italy historic agri-food buildings can be considered a relevant material expression and testimony of century-old agriculture and food processing practices handed down by generations. Recently they have gained ever-growing importance as a part of the wider architectural heritage. As such, they deserve dedicated general surveys to build a thorough knowledge of their distinctive characteristics and investigate their current condition, this way setting the basis for the implementation of planning and management actions for their sustainable valorisation. To this end, building information modelling (BIM) can be considered an efficient strategy to preserve construction information by creating 3D models based on surveys of the built heritage. To acquire in fast and accurate way geometric, reflectance and colour data of rural buildings, as 3D point-cloud, the terrestrial laser scanner (TLS) represents a powerful tool. The traditional TLS-based survey methods, in the context of historic agricultural buildings, have several limitations, mainly due to the presence of inaccessible parts and bulky machinery once used for processing and storage. In the present research, to overcome these issues and thus have a complete survey, we describe a proposal of an integrated methodology for obtaining 3D point-cloud data of existing rural agri-food buildings based on the integrated use of TLS, handheld scanner (HS), and unmanned aerial vehicles (UAV) instruments. The proposed methodology was tested in surveying three historic agri-food buildings and the accuracy of the obtained 3D point-cloud was calculated by means of the root mean square error (RMSE) on the X, Y, and Z alignment of the two different 3D point-clouds in correspondence of the used B/W target. Moreover, a measure of the distance between two merged 3D point-clouds, in their overlap area has been performed using the multiscale model to model cloud comparison (M3C2). RMSE analysis always shows values lesser than 1 cm and M3C2 shows values between 0 and about 6 cm.