Smart Agriculture Decision Making Scheme Using Quantum Annealing

Smart agriculture is introduced with the latest technologies to improve the overall agricultural production capacity and efficiency. This paper proposes a quantum-inspired decision making scheme for crop cultivation in smart agriculture. The goal of the scheme is to increase the farmers’ welfare by planting different types of crop on adjacent farmlands to achieve optimal balance of crop demand and production. The proposed scheme is modeled as a graph coloring problem, which is computationally hard to solve for large and complex graphs in general. By taking advantage of quantum-inspired metaheuristic approach, the graph coloring problem is formulated as Quadratic Unconstrained Binary Optimization (QUBO) model and solved by a quantum annealer. The experimental realization of the proposed method is investigated on D-Wave quantum annealing devices and its performance is compared with those of the brute-force and greedy algorithms. The experimental results show that the proposed decision making scheme achieves a higher success probability than the greedy algorithm and a much lower run time than the brute-force approach.