Smartphone sensors and Raspberry Pi devices combine to detect cosmic rays

Researchers in Japan have turned the cameras inside ordinary smartphones and Raspberry Pi computers into working cosmic ray detectors, demonstrating that consumer-grade CMOS image sensors can record the passage of energetic particles without any specialized hardware. The project, known as SORAMAME, is described in a study published on 1 July 2026 in Experimental Astronomy by Wakiko Takano, Shigeharu Udo, Atsushi Shiomi, and Kinya Hibino, a team spanning Kanagawa University and Nihon University. Their work shows that the same chips people use to take photographs can serve as low-cost particle detectors, opening the door to distributed cosmic ray observations by schools, hobbyists, and citizen scientists around the world.

Cosmic rays are everywhere. High-energy particles, mostly protons and atomic nuclei originating from sources both inside and far beyond our galaxy, constantly rain down on Earth's atmosphere, where they collide with air molecules and generate cascades of secondary particles that reach the ground. The primary particles themselves rarely make it to the surface; instead, it is their secondaries — chiefly muons, along with electrons, positrons, and photons — that permeate the environment in which we all live. A single muon passes through a patch of ground roughly the size of a fingernail every minute, which means that every person, every building, and every piece of electronics is continuously being traversed by particles born in collisions dozens of kilometers overhead. Despite this ubiquity, observing cosmic rays directly has traditionally required dedicated detection hardware — scintillators, photomultiplier tubes, drift chambers — that is expensive, bulky, and demanding to operate. That cost and complexity has effectively excluded schools, community groups, and other non-specialist settings from hands-on participation in cosmic ray science, a barrier the SORAMAME team set out to dismantle.

The key insight behind the project is that silicon CMOS image sensors, the light-detecting chips found in virtually every modern smartphone and tablet, are sensitive not only to photons but also to ionizing radiation. This is not an accident or a niche property: silicon is itself an ionization detector material, the same basic substance used in the pixel trackers of major particle physics experiments. When a charged particle such as a muon passes through the sensor, it deposits energy along its track, knocking electrons loose in the silicon lattice. The sensor's electronics collect that charge exactly as they would collect charge generated by incoming light, leaving behind a trail of bright pixels in an otherwise dark image. The result, when a phone is left with its camera covered and its exposure running, is a slow accumulation of elongated streaks — each one the fingerprint of a particle that passed through the chip while the owner was not looking.

This principle had been explored before. Earlier efforts, including the Distributed Electronic Cosmic-ray Observatory (DECO), developed at the University of Wisconsin, and proposals by physicists such as Daniel Whiteson and Michael Mulhearn, demonstrated the feasibility of smartphone-based particle detection and proved that camera apps could identify candidate events on consumer hardware. Those pioneering projects established that the concept worked in the lab and in the hands of early volunteers. SORAMAME builds on this foundation with a complete, user-friendly system designed for real-time observation, aiming to move the idea from a clever demonstration toward a sustainable, networked platform that ordinary users can operate continuously without expertise.

The researchers developed a smartphone and tablet application that repurposes the built-in camera as a particle detector, requiring no additional equipment. The app handles the entire detection pipeline on the device itself. First, the sensor is calibrated to characterize its baseline response, accounting for the fact that each individual chip has its own pattern of hot pixels and fixed-offset variations. Then noise filtering algorithms suppress thermal noise and other spurious signals that could masquerade as particle hits — a critical step, since the charge released by a single muon is tiny compared with the dynamic range the sensor was designed to handle for photography. Finally, track-candidate detection software scans each frame for the distinctive elongated clusters of bright pixels that indicate a particle traversal, separating these linear signatures from the compact blobs produced by thermal fluctuations or from uniform glow caused by stray light. Events identified on the device are recorded and visualized in real time, allowing users to watch particle tracks accumulate as they happen — an immediate, tangible encounter with invisible radiation that the researchers hope will be a powerful educational experience.

Beyond the on-device processing, SORAMAME incorporates cloud-based data management. Individual detections are uploaded and aggregated, enabling visualization across the whole network of participating devices. A public web dashboard operated from Kanagawa University displays the collected data, and the source code for both the smartphone application and the Raspberry Pi camera analysis has been released publicly on GitHub. This open approach serves two purposes at once: it allows other researchers and educators to inspect, adapt, and improve the software, and it builds the transparency that citizen science projects need if their data are ever to be trusted by the wider scientific community. The architecture reflects the project's dual ambition: to serve as an educational tool in the near term, and to mature into a platform for genuine large-scale data collection as the number of participating devices grows.

To validate the system's performance, the team carried out measurements under conditions where cosmic ray flux varies in well-understood ways. Because the intensity of cosmic rays reaching a detector depends strongly on altitude — the atmosphere acts as a shield, so flux increases as one ascends — and on latitude, a consequence of geomagnetic shielding by Earth's magnetic field, any detector claiming cosmic ray sensitivity should reproduce these known variations. At commercial cruising altitudes of around ten kilometers, the secondary particle flux is many times higher than at sea level, because far less atmosphere remains above the detector to absorb the shower. At the same time, Earth's magnetic field bends the paths of charged primary particles, deflecting more of them away from the equator than from the poles, where field lines run nearly vertically and offer the least resistance. The researchers performed in-flight measurements, operating their devices aboard aircraft where the particle flux is significantly higher than at sea level, and they conducted additional measurements using Raspberry Pi devices equipped with camera modules, including the Raspberry Pi High Quality Camera built around Sony's IMX477 sensor. The Raspberry Pi platform, inexpensive and easily deployed in a fixed configuration, offers a useful complement to smartphones: its camera can be run continuously under stable conditions, making it attractive for semi-permanent monitoring stations in classrooms or amateur observatories.

The results were encouraging. Both the in-flight smartphone data and the Raspberry Pi-based measurements captured altitude- and latitude-dependent variations in particle flux consistent with expectations from geomagnetic shielding. In other words, the detectors saw more particles at higher altitudes, and the flux pattern across latitudes reflected the way Earth's magnetic field deflects incoming charged particles more effectively near the equator than near the poles. For sensors never designed for particle physics, reproducing these signatures constitutes a meaningful demonstration that the observed events are genuinely cosmic ray induced rather than systematic artifacts. Noise sources — thermal dark current, sensor defects, electronic interference — do not respect altitude or latitude; only real radiation should vary in precisely the way theory predicts. The team has also previously reported aspects of this approach at the International Cosmic Ray Conference, the field's principal global gathering, laying groundwork for the present publication.

The success of the approach rests in part on careful attention to sensor characteristics. The researchers drew on detailed analyses of commercial sensor hardware, including the Sony IMX703 stacked CMOS sensor used in the iPhone 13 Pro's main camera, which features a pixel pitch of 1.9 micrometers. That fine pixel granularity matters: the smaller the pixel, the more finely a particle track is sampled, and the more reliably its elongated shape can be distinguished from round noise clusters. Stacked sensor designs, in which the photodiode layer is fabricated above dedicated circuitry layers, also influence how charge generated by a passing particle spreads between neighboring pixels. Understanding pixel geometry, noise behavior, and charge collection properties is essential for distinguishing genuine particle tracks from false positives, and the calibration and filtering steps built into the SORAMAME application reflect this sensor-level understanding.

The researchers are candid about the limitations inherent in their platform. Consumer-grade sensors were engineered for photography, not radiation detection: they lack the timing precision, active area, shielding, and readout speed of purpose-built detectors. A single smartphone cannot reconstruct particle energies or directions with the accuracy demanded by professional cosmic ray observatories, and the thin active silicon layer of a camera chip intercepts only a small fraction of the particles crossing it, limiting raw efficiency. Individual detections from an unshielded phone also carry risks of misidentification, since some image artifacts may mimic particle tracks. These constraints mean that SORAMAME's scientific value depends on scale and statistical aggregation across many devices rather than on the precision of any single instrument.

It is precisely that scale which makes the approach compelling. According to industry statistics cited by the authors, the number of internet-connected Internet of Things devices worldwide has been growing rapidly and is projected to continue expanding through the coming decades, and an unprecedented fraction of those devices carry silicon CMOS image sensors. If even a small share of the world's smartphones participated in cosmic ray observation, the resulting network would dwarf any professional array in geographic coverage and detector count. Distributed networks of modest detectors have a distinguished history in the field: continental-scale observatories such as the Pierre Auger Observatory in Argentina and the Telescope Array in Utah spread hundreds of surface detectors over thousands of square kilometers precisely because the largest and most energetic air showers strike the ground over enormous areas and cannot be captured by any single instrument. A global mesh of smartphone detectors could, the authors suggest, contribute to future scientific breakthroughs — particularly in areas such as monitoring extensive air showers, where particle cascades strike the ground over broad areas and benefit enormously from many spatially separated observation points. A dense, worldwide network would also provide continuous monitoring of the ground-level radiation environment, potentially useful for studying solar-driven variations and atmospheric phenomena such as thunderstorm-related particle bursts, which remain active topics of research.

The nearer-term payoff is educational. Inquiry-based learning benefits when students can collect their own data rather than reading about experiments performed elsewhere, and SORAMAME gives classrooms a working cosmic ray observatory for free. Because the app records and displays particle-like events in real time, a lesson can become an actual measurement session, with students comparing flux readings taken at different altitudes, indoors versus outdoors, or on devices at different geographic latitudes.