This project focuses on developing a cloud-based digital platform integrated with a Decision Support System (DSS) for investment analysis in Controlled Environment Agriculture (CEA), with subsequent adaptation for other production systems. The initial platform will support various CEA setups such as traditional greenhouses using hydroponics or aquaponics, including tools for analyzing investments in bioreactors that recycle organic waste, which may originate from the production process itself or be integrated with other production systems like poultry farming. The platform aims to enhance investment efficiency, sustainability, and profitability by providing comprehensive economic feasibility assessments, including cash flow analysis, cost evaluations, income statements, ROI projections, and scenario and sensitivity analyses. It employs a probabilistic modelling framework using Bayesian Network (BN) simulation which supports decision-making under uncertainty and can integrate expert knowledge to accommodate data limitations. Successful commercialization of the platform could identify economically viable and sustainable investment options, resulting in increased investment efficiency through reduced or better-managed uncertainty and better financial planning.
Research Objectives:
- Develop a digital platform that delivers comprehensive financial projections and risk analysis to enhance economic feasibility assessments for various Controlled Environment Agriculture (CEA) setups and waste treatment methods, aimed at transforming organic waste into fertilizer across multiple industries
- Integrate advanced statistical models to manage data uncertainties and improve strategic decision-making in investment planning.
- Enable users to input data, switch between scenarios, and visualize the impacts of varying conditions on financial viability, thereby increasing investment efficiency by identifying feasible and sustainable options.