Opportunistic sensing: Unattended acoustic sensor selection using crowdsourcing models

Unattended wireless sensor networks have been widely used in many applications. This paper proposes automatic sensor selection methods based on crowdsourcing models in the Opportunistic Sensing framework, with applications to unattended acoustic sensor selection. Precisely, we propose two sensor selection criteria and solve them via greedy algorithm and quadratic assignment. Our proposed method achieves, on average, 5.64% higher accuracy than the traditional approach under sparse reliability conditions.