Slocalization: Sub-{\mu}W Ultra Wideband Backscatter Localization

Ultra wideband technology has shown great promise for providing high-quality location estimation, even in complex indoor multipath environments, but existing ultra wideband systems require tens to hundreds of milliwatts during operation. Backscatter communication has demonstrated the viability of astonishingly low-power tags, but has thus far been restricted to narrowband systems with low localization resolution. The challenge to combining these complimentary technologies is that they share a compounding limitation, constrained transmit power. Regulations limit ultra wideband transmissions to just -41.3 dBm/MHz, and a backscatter device can only reflect the power it receives. The solution is long-term integration of this limited power, lifting the initially imperceptible signal out of the noise. This integration only works while the target is stationary. However, stationary describes the vast majority of objects, especially lost ones. With this insight, we design Slocalization, a sub-microwatt, decimeter-accurate localization system that opens a new tradeoff space in localization systems and realizes an energy, size, and cost point that invites the localization of every thing. To evaluate this concept, we implement an energy-harvesting Slocalization tag and find that Slocalization can recover ultra wideband backscatter in under fifteen minutes across thirty meters of space and localize tags with a mean 3D Euclidean error of only 30 cm.Comment: Published at the 17th ACM/IEEE Conference on Information Processing in Sensor Networks (IPSN'18

SociTrack: Infrastructure-Free Interaction Tracking through Mobile Sensor Networks

Social scientists, psychologists, and epidemiologists use empirical human interaction data to research human behaviour, social bonding, and disease spread. Historically, systems measuring interactions have been forced to choose between deployability and measurement fidelity—they operate only in instrumented spaces, under line-of-sight conditions, or provide coarse-grained proximity data. We introduce SociTrack, a platform for autonomous social interaction tracking via wireless distance measurements. Deployments require no supporting infrastructure and provide sub-second, decimeter-accurate ranging information over multiple days. The key insight that enables both deployability and fidelity in one system is to decouple node mobility and network management from range measurement, which results in a novel dual-radio architecture. SociTrack leverages an energy-efficient and scalable ranging protocol that is accurate to 14.8 cm (99th percentile) in complex indoor environments and allows our prototype to operate for 12 days on a 2000mAh battery. Finally, to validate its deployability and efficacy, SociTrack is used by early childhood development researchers to capture caregiver-infant interactions

Grid Watch: Mapping Blackouts with Smart Phones

The power grid is one of humanity’s most significant engineering undertakings and it is essential in developed and developing nations alike. Currently, transparency into the power grid relies on utility companies and more fine-grained insight is provided by costly smart meter deployments. We claim that greater visibility into power grid conditions can be provided in an inexpensive and crowd-sourced manner independent of utility companies by leveraging existing smartphones. Our key insight is that an unmodified smartphone can detect power outages by monitoring changes to its own power state, locally verifying these outages using a variety of sensors that reduce the likelihood of false power outage reports, and corroborating actual reports with other phones through data aggregation in the cloud. The proposed approach enables a decentralized system that can scale, potentially providing researchers and concerned citizens with a powerful new tool to analyze the power grid and hold utility companies accountable for poor power quality. This paper demonstrates the viability of the basic idea, identifies a number of challenges that are specific to this application as well as ones that are common to many crowd-sourced applications, and highlights some improvements to smartphone operating systems that could better support such applications in the future