Real-time human-to-machine and machine-to-machine interactions at the edge of the Internet are the key drivers for research in high-speed and low-latency wireless communication. In order to meet the most stringent latency demands, such interactions should be carried out autonomously by groups of nodes at the edge, potentially resorting to specialized physical layer techniques. While past research has mostly focused on 5G cellular network technology, we assess the feasibility to utilize IEEE 802.11 (Wi-Fi) technology for this purpose. In contrast to existing work on macrodiversity schemes to enhance network capacities, we highlight the potential of macrodiversity to reduce the latency in one-to-many communication scenarios through concurrent network flooding. To this end, we study the practical feasibility of concurrent transmissions with IEEE 802.11, while taking the characteristics of both the DSSS PHY and the OFDM PHY of IEEE 802.11 into account. In particular, we quantify the impact of the limiting factors that impair the decodability of concurrent \mbox{Wi-Fi} transmissions and analyze their combined effects in simulations and practical SDR testbed experiments. In doing so, we also assess the capability of commodity hardware to decode concurrent Wi-Fi transmissions while deliberately introducing signal impairments by tuning the limiting factors. With this, we identify the key parameter limits to enable low-latency flooding at the edge with IEEE 802.11.