Radon is a naturally occurring radioactive gas and is the second leading cause of lung cancer after smoking tobacco. Its invisible and odorless nature often leads to it going undetected, posing a significant health threat in susceptible areas, especially schools. Although traditional mitigation strategies are reasonable for smaller private properties, their cost can become prohibitively expensive and difficult for older and larger buildings. We propose, build, and test a cost-effective, sustainable mitigation strategy that uses the existing HVAC infrastructure of susceptible buildings to remove radon before occupancy hours. We compare this to a naive approach and find that we can save time on HVAC operation and keep radon levels to an acceptable low.

Radio astronomy observatories examine the universe by capturing faint RF signals from space. The equipment to capture these signals is extremely sensitive, and nearby transmitters, such as LEO satellites, cause destructive interference. We propose the Spectra watermarking protocol to add an identifying fingerprint to these interfering transmitters. Spectra changes the timing of key transmissions to encode identifying information that can be decoded by examining transmission timestamps and without having to demodulate the actual transmission. We implement multiple forward error correction codes for Spectra to account for dynamic LEO satellite channels. We evaluate Spectra and show that it can operate over highly variable channels with low BER while preserving the network performance of the interfering device.

Underwater acoustic networks (UANs) have the potential to benefit greatly from advances in in-band full-duplex (IBFD) communication, as this would reduce packet collisions and timing overhead from link layer protocols. A major direction of research to achieve IBFD has been through self-interference cancellation (SIC), a process that tries to minimize the effect of self-interference (SI) caused by a device's own transmission when it is trying to receive a packet from another device. Active SIC techniques, however, can be costly in computation and energy resources. The chirp spread spectrum (CSS) modulation scheme, which already provides noise- and multipath-resistant communication in UANs, can also provide a novel solution for simplified IBFD communication. In this paper, we use orthogonal CSS to enable IBFD communication that requires absolutely no SIC filtering when the signal of interest (SOI) is within -20 dB of the power of the self-interference (SI). For situations where the SOI is weaker than -20 dB of the power of the SI, we also provide a computationally light SIC filter that maintains clear communication.

This work proposes an exploratory system of network addressing and management for a fleet of autonomous underwater vehicles (AUVs). As fleets of AUVs become more common and their tasks more diverse, it become necessary to manage them more at the network layer, handling new group formations and organization. As groups form and re-form during missions, there needs to be a way to identify a particular AUV and its role in the entire network. This work proposes one such network-level addressing system for a fleet of AUVs, the Fleet Protocol (FP) addressing system.

Vehicle-to-Everything (V2X) technologies are seeing dramatic growth as smart cities join the Internet of Things (IoT). Overseeing the adoption of this technology, governing bodies such as State Departments of Transportation (DOTs) are starting to contemplate Vehicle-to-Infrastructure (V2I) deployments, and they need to know which V2I devices will perform best in their specific jurisdictions. In this paper, we develop several methods to test commercial, off-the-shelf (COTS) Cellular-V2X (C-V2X) roadside units (RSUs) as a way to inform government deployment. These methods compare performance between different COTS RSUs side-by-side. We present these methods all together as an open source framework which evaluates an RSU multilaterally: at specification compliance, network management, and transmission range layers.

Sharing crowded radio spectrum with astronomical observatories and other passive users requires a multilayer approach. We present a protocol that allows passive devices to notify nearby active users of their spectrum utilization plans, regardless of the wireless protocol used by the receiver. For non-compliant active users, we use a Hadamard projection based cancellation algorithm to remove residual interference. Hadamard projection can be implemented before additional stages of RFI rejection such as subspace projection that may occur during beamforming and imaging. The integrated system is demonstrated with laboratory and outdoor over the air experimental results. The system is able to preserve a signal of interest to the passive user while suppressing interference from both compliant and non-compliant active spectrum users.

IEEE 802.11 (WiFi) only has two modes of trust—complete trust or complete untrust. The lack of nuance leaves no room for sensors that a user does not fully trust but wants to connect to their network, such as a WiFi sensor. Solutions exist, but they require advanced knowledge of network administration. We solve this problem by introducing a new way of modulating data in the latency of the network, called Latency Shift Keying. We use specific characteristics of the WiFi protocol to carefully control the latency of just one device on the network. We build a transmitter, receiver, and modulation scheme that is designed to encode data in the latency of a network. We develop an application, Wicket, that solves the WiFi trust issue using Latency Shift Keying to create a new security association between an untrusted WiFi sensor and a wired device on the trusted network. We evaluate its performance and show that it works in many network conditions and environments.

LEO satellite constellations have changed the world for the better through Earth observations, research, and telecommunications. Recent advances, especially in telecommunications, have brought the world closer to global connectivity. While these constellations usually have intra-network communications, they generally lack inter-network communication with other networks which leads to interference and noise. This interference and noise leads to degradation of network performance. We propose Ghost Modulation (GM), a novel protocol, to enable inter-network communication and spectrum coordination between a LEO satellite and any other device that supports the GM protocol. GM changes the transmission timing of key packets to encode data while passing most packets through. We evaluate our protocol and show that it can be used to dynamically coordinate heterogeneous networks with minimal overhead.

Air quality has important climate and health effects. There is a need, therefore, to monitor air quality both indoors and outdoors. Methods of measuring air quality should be cost-effective if they are to be used widely, and one such method is low-cost sensors (LCS). This study reports on the use of LCSs in Ulaanbataar, Mongolia to measure PM2.5 concentrations inside yurts or “gers”. Some of these gers were part of a non-government agency (NGO) initiative to improve insulating properties of these housing structures. The goal of the NGO was to decrease particulate emissions inside the gers; a secondary result was to lower the use of coal and other biomass material. LCSs were installed in gers heated primarily by coal, and interior air quality was measured. Gers that were modified by increasing their insulating capacities showed a 17.5% reduction in PM2.5 concentrations, but this is still higher than recommended by health organizations. Gers that were insulated and used a combination of both coal and electricity showed a 19.1% reduction in PM2.5 concentrations. Insulated gers that used electricity for both heating and cooking showed a 48% reduction in PM2.5 but still had higher concentrations of PM2.5 that were 6.4 times higher than recommended by the World Health Organization (WHO). Nighttime and daytime trends followed similar patterns and trends in PM2.5 concentrations with slight variations. It was found that at nighttime the outside PM2.5 concentrations were generally higher than the inside concentrations of the gers in this study, meaning that PM2.5 would flow into the ger whenever the doors were opened, causing spikes in PM2.5 concentrations.

Community-driven sensor networks have been instrumental in providing easy access to affordable, large-scale measurement recording, facilitated by the accessibility of inexpensive sensor hardware. The simplicity of this hardware makes it challenging to retrieve trustworthy location data without added hardware such as GPS. We introduce the LaMDA framework, a software-based solution run solely in a web browser to determine the location of a device with the aid of a registering device. We monitor the device for any location changes by analyzing its traceroute data from a central server. Our solution allows minimal firmware changes to be made to fleets of devices without recall or changes to hardware.

Vehicle-to-Everything (V2X) technologies are seeing significant growth as an element of smart cities and a more-interconnected digital world in the Internet of Things (IoT). As governing bodies like State Departments of Transportation (DOTs) contemplate Vehicle-to-Infrastructure (V2I) deployments, they need to know what V2I devices will perform best, both in general and in their specific jurisdictions. In this paper, we develop a method to test commercial, off-the-shelf (COTS) Cellular-V2X (C-V2X) roadside equipment (RSE) as a way to inform government deployment; this includes indoor and outdoor tests for thoroughness. While this method needs to be refined, it provides a strong basis for future DOTs to determine which devices will best meet their deployment needs.

Commercial Internet of Things (IoT) sensors enable continuous data collection that benefits exposomic studies. The Exposure Health Informatics Ecosystem (EHIE) is one such sensor-based informatics platform for performing multiple simultaneous exposomic studies. It captures data from networks of sensors designed to record air quality in homes of the study’s participants and neighboring areas. In such cases where sensors are continually streaming data, it is crucial to monitor, in real time, the operational status of the network and record possible anomalies. Data collected by these sensors is only useful if it is free of errors. Therefore, maintaining the proper integrity of devices requires the capture of all deployment events that can cause anomalies. Tracking faults by recording system metadata is a difficult task, and we need a mechanism to capture the trajectories of devices within and across studies, systematically capture metadata of deployed version, and assign appropriate provenance to data recorded from each sensor. In this paper, we propose the use of a permissioned blockchain to manage the metadata and connect seemingly unrelated changes to create a trajectory of events that could result in the errors we observe. We implement a preliminary version of our blockchain solution in Hyperledger Fabric to help track errors in such a volatile setup. We also highlight how the properties of blockchain fulfill the essential needs for a metadata management solution needed in our case study.

The health hazard of air pollution in developing countries poses a significant threat of cardiovascular, respiratory, and other diseases. Ulaanbaatar, Mongolia is among cities with the worst polluted air in the world due to the use of coal as the primary heating source in the traditional Mongolian gers where most of the local population resides. Humanitarian groups are looking for ways to improve air quality, but are unable to measure the effects of their solutions. We build a low-cost air quality sensor that can upload data in real-time in remote locations. This newly developed sensor allows for _real-time_ air quality monitoring and tracking that was not possible before in such locations. We present the implementation and deployment of this system and share experiences and lessons learned from deploying the sensors in such a unique location.

We design and build a protocol called on-off noise power communication (ONPC), which modifies the software in commodity packet radios to allow communication, independent of their standard protocol, at a very slow rate at long range. To achieve this long range, we use the transmitter as an RF power source that can be on or off if it does or does not send a packet, respectively, and a receiver that repeatedly measures the noise and interference power level. We use spread spectrum techniques on top of the basic on/off mechanism to overcome the interference caused by other devices' channel access to provide long ranges at a much lower data rate. We implement the protocol on top of commodity WiFi hardware. We discuss our design and how we overcome key challenges such as non-stationary interference, carrier sensing and hardware timing delays. We test ONPC in several situations to show that it achieves significantly longer range than standard WiFi.

We design and build EpiFi, a novel architecture for in-home sensor networks which allows epidemiologists to easily design and deploy exposure sensing systems in homes. We work collaboratively with pediatric asthma researchers to design multiple studies and deploy EpiFi in homes. Here, we report on experiences from two years of deployments in 15 homes, of two different types of studies, including many deployments continuously monitored over the past 11 months. Based on lessons learned from these deployments and researchers, we develop a new mechanism for sensors to bootstrap their connectivity to a subject's home WiFi router and implement data reliability mechanisms to minimize loss in the network through a long-term deployment.

Air quality is important, varies across time and space, and is largely invisible. Pioneering past work deploying air quality monitors in residential environments found that study participants improved their awareness of and engagement with air quality. However, these systems fielded a single monitor and did not support user-specified annotations, inhibiting their utility. We developed MAAV– a system to Measure Air quality, Annotate data streams, and Visualize real-time PM2.5 levels – to explore how participants engage with an air quality system addressing these challenges. MAAV supports collecting data from multiple air quality monitors, annotating that data through multiple modalities, and sending text message prompts when it detects a PM2.5 spike. MAAV also features an interactive tablet interface for displaying measurement data and annotations. Through six long-term field deployments (20-47 weeks, mean 37.7 weeks), participants found these system features important for understanding the air quality in and around their homes. Participants gained new insights from between-monitor comparisons, reflected on past PM2.5 spikes with the help of their annotations, and adapted their system usage as they familiarized themselves with their air quality data and MAAV. These results yield important insights for designing residential sensing systems that integrate into users’ everyday lives.

When several internet-of-things devices are required to be installed in a smart home, significant effort is required to provide each device with the association information for the home's wireless router. We design and build a novel protocol called Secure Transfer of Association Protocol (STRAP), which securely bootstraps connectivity between a set of deployed WiFi devices and a home's wireless router. We show that STRAP works in a variety of environments and is faster than conventional methods for connecting WiFi devices to home wireless routers.