Modeling Artificial Intelligence Of Things On Blockchain to Improve Supply Chain Security

Today, due to international sanctions, fierce competition, the prevention of fraud, and competition between goods producing units, the importance of data and information networks has led to pushing goods-producing units to use Internet of Things tools. Supply chain management systems have widely developed smart tools as a platform for the production and storage of big data, facilitating communication between various components and enhancing their overall security. This paper aims to introduce a mathematical model that utilizes Internet of Things tools connected to the blockchain, leveraging artificial intelligence (AIoT) to reduce costs, prevent fraud, and enhanc supply chain security. Considering the importance of medicine fraud, a mathematical model was implemented using artificial intelligence algorithms in a real case study of the pharmaceutical supply chain. The results of solving the mathematical model showed that Internet of Things tools have led to 8.5% profitability in operating costs related to fraud detection and drug security, despite the increase in total costs. Also, the numerical examples showed that the gray wolf algorithm has a higher efficiency in achieving optimal results. The average time to solve the mathematical model with genetic algorithm is 106.46 seconds, with particle swarm optimization algorithm is 111.39 seconds, and with gray wolf algorithm is 123.64 seconds .Gray wolf algorithm has resulted in a 0.5% improvement in total supply chain costs with a 16% increase in resolution time. The proposed model can be useful to prevent fraud and increase the security of Iran's food or pharmaceutical supply chain.