  This paper presents the design, implementation, and operation of a novel
distributed fault-tolerant middleware. It uses interconnected WSNs that
implement the Map-Reduce paradigm, consisting of several low-cost and low-power
mini-computers (Raspberry Pi). Specifically, we explain the steps for the
development of a novice, fault-tolerant Map-Reduce algorithm which achieves
high system availability, focusing on network connectivity. Finally, we
showcase the use of the proposed system based on simulated data for crowd
monitoring in a real case scenario, i.e., a historical building in Greece (M.
Hatzidakis' residence).The technical novelty of this article lies in presenting
a viable low-cost and low-power solution for crowd sensing without using
complex and resource-intensive AI structures or image and video recognition
techniques.
