# Skyfall: Signal Fusion from a Smartphone Falling from the Stratosphere
## 1 Introduction  
The rapidly expanding capabilities of sensor systems in smartphones makes them viable Internet of Things (IoT) platforms [1] and has fueled their adoption as data collection systems. These mobile commercial off-the-shelf (COTS) cyber-physical systems [2] are well suited for constructing low size, weight, power, and cost (low SWaP-C) distributed sensor networks [3; 4; 5; 6; 7; 8; 9; 10; 11; 12; 13; 14; 15; 16; 17; 18; 19; 20]. Early studies [3] concentrated on possibilities, whereas more recent studies focus on specific use cases. Some applications center on biosignals [4; 5; 6; 7], improvements in geolocation [8; 9; 10], and educational or citizen science [11; 12; 13; 14; 15]. Our work contributes to the growing environmental and disaster monitoring IoT [1] at regional and global scales [16; 17; 18; 19; 20; 21; 22; 23; 24; 25]. All of these efforts have been aided by the rapid increase in processor speeds and dynamic range of on-board sensors, which have improved signal quality and reduced signal latency. One of the key disaster monitoring IoT applications is explosion monitoring. The basic concept of operation is that smartphones with optimized settings could use their internal sensors to provide useful information about the environmental impact of an explosive blast [20]. We present smartphones as an efficient technical solution for exploratory studies and to provide additional information for observational gaps. A variety of infrasound and geoacoustic monitoring scenarios have been evaluated since 2014 [20], with successful collection and analysis of explosive signals varying from small-yield surface detonations (e.g., [21]) to the 2022 multi-megaton eruption blast from the Hunga Tonga volcano [22]. This paper reports the results of an experiment designed to record surface explosions from high-altitude balloons. This is a viable concept of operation for remote environmentalmonitoring on Earth and Venus (e.g., [24]). The balloon flew up to \(\sim\)36 km into the stratosphere, about 3.6 times the nominal 10 km cruising altitude of commercial aircraft. Despite the ambient low pressure and subzero temperatures, the smartphone acoustic and acceleration sensors picked up the explosion signal [23], and all sensors recorded the rapid, turbulent descent and ground impact. The very survivability of a smartphone operating and falling from stratospheric heights is noteworthy and a testament to the present-day ruggedness of these platforms. We present the first published smartphone measurements in the stratosphere; the first smartphone observations of the dynamics of a sensor system falling through the stratosphere and troposphere and impacting the ground; and the first airborne smartphone multimodal sensor fusion and validation with external geospatial and barometric sensor systems. At the time of writing, the explosion signal data are embargoed. However, the data from the balloon's descent through the stratosphere and troposphere (the Skyfall), and its impact with the ground, are openly available and have much higher signal diversity. Although the key application is disaster (e.g., explosion) monitoring IoT, one of our main motivations is educational. Various students, engineers, and researchers have requested practical advice on how to access, process, and integrate smartphone multi-sensor data. This paper addresses this knowledge gap by describing the Skyfall stage in detail and providing open-source methods to perform multi-sensor data fusion to reconstruct the descent timeline. Our intended audience are researchers, engineers, early-career, and citizen scientists interested in a hands-on guide to the present data-gathering capabilities of smartphones and the resulting types of data structures. Due to the breadth of the intended audience, we have made substantial efforts to make this paper accessible. The next section provides a summary of the systems, sensors, and signals that define this work. Section 3 presents the materials and methods available to the reader to reproduce our results.