Disaster Mitigation Using a Peer-to-Peer Near Sound Data Transfer System R. Padma Priya , Ritumbhara Bhatnagar , and Shaaran Lakshminarayanan 1 Introduction When we consider managing and saving crowds in the times of crisis, for instance indoor fire hazards or natural calamities (floods, earthquakes, etc.), the lack of access to crucial information and failure to access help at a concerned area normally happens due to compromised network towers or servers. Additionally, in view of the ongoing COVID-19 pandemic and pre-empting any other pandemic in the near future, we have taken into consideration the concept of social distancing to manage crowds in places of hazards effectively. We aim to solve this problem with the help of largely, near sound data transfer (NSDT) technology along with peer-to-peer (P2P) networking. Sound is a great medium to transfer data when it comes to proximity, taking in view the high speed and no need of an external setup. This is the reason many industries are using NSDT to transfer crucial data within their own premises. NSDT concerns itself with transmission of data over near sound frequencies, for instance over ultraviolet rays. This technology has gained popularity over the past three to four years, and such efforts to increase data transfer rate using NSDT have been promising, through one such technology “ChirpCast: Data Transmission via Audio” [1]. Chirp Software Development Kit (SDKs) have made it very easy for developers to send data over audio. Data is provided to the SDKs in the form of an array of bytes [1]. Transmission of the data can be via audible or inaudible ultra- sonic audio depending on the configuration of the Chirp SDK [2]. Another breakthrough, LISNR is an advanced, near ultrasonic, ultra-low power data trans- mission technology that enables fast, reliable, and secure communication between devices via a speaker and/or microphone [3]. A device enabled with LISNR soft- R. Padma Priya (&) Á R. Bhatnagar Á S. Lakshminarayanan School of Computer Science and Engineering, Vellore Institute of Technology, Vellore, Tamil Nadu, India e-mail: padmapriya.r@vit.ac.in © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022 R. R. Raje et al. (eds.), Artificial Intelligence and Technologies, Lecture Notes in Electrical Engineering 806, https://doi.org/10.1007/978-981-16-6448-9_36 353