Plant secondary metabolites are critical factors that aid plants in adaptation to their environment and are important sources of pharmaceuticals. Growth environment chambers nowadays are employed only to improve the overall production of the plant, while paying less attention to its quality. Automated strategies can be applied to attune the existing model, making it compatible for precisely controlling the environmental factors, which are the significant effectors of changes in the metabolic pathways of secondary metabolites. Previously, MIT has developed a Personal Food Computer (PFC) to control the growth environment of plants to maintain uniformity in their production in an urban setting. However, several challenges remained untouched, especially when the PFC was used in a research setting. One such instance was that an increase in the daylight negatively impacted the level of humidity, which could be undesirable and requires manual intervention to maintain grow-condition stability. To overcome the shortcomings of the existing model we have modified MIT's PFC by implementing cloud-based flexible automation techniques along with robotics to develop a Cost-Effective Automated Food Computer (CEAFC). The present article is aimed at addressing the automated features of CEAFC and its eloquent use in the production of secondary metabolites of therapeutic value.