Abstract

Global pandemics significantly disrupt local food supply chains as was evident at the peak of the Corona Virus Disease 2019 (COVID-19). COVID-19 lockdowns adversely affected food security among mostly the poor and vulnerable. Limited interactions among farmers, inputs providers, food processors, transporters, and retailers negatively affected the provision of food. To cab food shortages, implementing the Internet of Things (IoT) based household Aquaponics in order to ensure sustainable food production, is a potentially viable solution.  

Ordinarily, poor and vulnerable households are digitally illiterate. Privacy concerns adversely influence the adoption of IoT-based automation. Consequently, guaranteeing security by default among the digitally illiterate becomes necessary to improve IoT adoption. A potential solution is utilizing an architecture that ensures “Privacy by Design” in addressing IoT privacy concerns. We propose an “offline-first” architecture for automated and low-cost household Aquaponics units. The privacy-preserving architecture moves machine learning, data storage, and computation away from cloud platforms into privacy-preserving, community-hosted fog and edge computing platforms.