Digital twins for vertical farming

食品自主权是魁北克省和加拿大的一个重要问题。与此同时，自1960年以来，加拿大的人口一直以每年30多万人的速度稳步增长。不适当的粮食自主权对加拿大的可持续发展构成严重威胁，因此对魁北克也构成威胁。在魁北克，实现可持续粮食自主的主要挑战是四季气候，这阻碍了全年露天农业。控制环境农业（CEA）主要与垂直农业相关，为应对当地粮食生产的担忧和挑战提供了可持续的解决方案。CEA通过一种资源和成本效益的解决方案，在封闭和受控的环境中生产蔬菜和水果，使用人工照明和管理环境条件。Ferme d'Hiver是一家位于魁北克的领先公司，致力于在环境控制的生长环境中生产反季，高营养的水果和蔬菜，不使用化学农药。Ferme d'Hiver的目标是通过整合各种尖端技术来自动化生产系统，并通过回收垂直农业灯产生的热量来加热邻近的温室，从而优化其运营的产量和能源消耗。这个项目的目标是研究应用数字阴影来模拟生物体的行为，以分析和控制它们的生命周期的可行性。数字阴影允许模拟生产周期和探索各种场景，以优化生产系统。尽管已经与网络物理系统结合应用，但将数字阴影用于植物等生物有机体仍然是一个挑战。因此，该项目通过扩展物理资产的定义，为开发以生物有机体为特征的系统的数字阴影提供了手段。

Food autonomy is an importnt concern in Quebec and Canada. At the same time, the population of Canada has been steadily increasing by over 300,000 per annum since 1960. Inappropriate food autonomy poses serious threats to the sustainable development of Canada and, as a consequence, of Quebec. In Quebec, the main challenge to achieve sustainable food autonomy is the four-season climate that prevents year-round open-air farming. Controlled Environment Agriculture (CEA), chiefly associated with Vertical Farming, offers a sustainable solution to cope with the concerns and challenges of local food production. CEA archives this by a resource and cost efficient solution to produce vegetables and fruits in a closed and controlled environment, using artificial lighting and managed environmental conditions. Ferme d'Hiver is a leading Quebec-based company targeting the production of off-season, high-nutrition fruits and vegetables in an environmentally controlled growth environment, without the use of chemical pesticides. Ferme d'Hiver aims at optimizing the yield and the energy consumption of its operations by integrating various cutting-edge technologies to automate its production system and by recovering the heat produced by the vertical farming lights to heat adjacent greenhouses. The goal of this project is to investigate the feasibility of applying Digital Shadows for modeling the behavior of living organisms for the analysis and control of their lifecycle. Digital Shadows allow the simulation of the production cycle and the exploration of various scenarios for the optimization of the production system. Although already applied in conjunction with cyber-physical systems, the use of digital shadows for biological organisms such as plants remains a challenge. Therefore, this project provides means for developing Digital Shadows of systems featuring biological organisms by extending the definition of the physical asset.