Hardware provides driver authors both a strict specification of the operations a driver is allowed to do, and a highly permissive interface full of operations a driver can do. Authoring drivers that adhere to the provided hardware device protocol is challenged by dynamic definitions of what a driver should do based on the hardware's state. This is further complicated by increasingly capable hardware which may transition between states concurrently and independently from the software driver.

Online platforms are riddled with harassment, which significantly impacts the well-being of users. Unfortunately, the content moderation solutions provided by platforms often disappoint end-users as they fail to equip individuals with sufficient controls for their personal situations. In this work, the author, who personally experienced a sustained harassment campaign on Twitter, decided to regain control by constructing an automated, personalized, and collaborative anti-harassment system to protect herself, which has proven itself to be effective. The experience of developing—and re-developing in the face of repeated platform API changes and restrictions—this personalized content moderation system highlights many design issues that make managing severe online harassment such a challenge and invites critical study of the power dynamics between large online platforms and individual users. Through this analysis, this report aims to inform better designs to help platforms more effectively protect victims.

Wireless sensor networks (WSNs) deployed in the natural environment offer well-established benefits for prediction, modeling, timely response, and informed decision making in the face of the accelerating climate crisis. To facilitate faster experimentation and deployment, researchers have focused on developing WSN platforms that support rapid prototyping and field readiness. Despite their potential, these platforms have historically seen limited uptake both among domain scientists and the broader IoT research community. In this paper, we present insights gained from the development of ENTS (Environmental NeTworked Sensing)—a WSN platform co-designed with three distinct groups of domain scientists through an iterative development process. We describe the evolution of ENTS from a simple analog measurement tool to an extensible platform actively supporting collaborations with diverse domain experts. We synthesize our experience into a set of design principles aimed at fostering impactful and lasting research partnerships. Finally, we instantiate the outlined design principles for future interdisciplinary sensing efforts, including open-source hardware, firmware, low-cost custom weatherproof enclosures, and a web-based visualization tool.

With the widespread deployment of Bluetooth Low Energy (BLE) enabled devices, we are moving towards a world full of distributed, resource-constrained devices. With this growth comes the challenge of maintaining and communicating with millions of intermittently connected low-power BLE devices. While sending data from these BLE devices back to central servers has successfully been realized at scale (e.g. Apple AirTags), downlink communication is more difficult. Given the common usage of BLE-only devices in public infrastructure and other safety-critical environments, this inability to communicate with devices in a timely manner poses a barrier to realizing safe and secure ubiquitous computing. We explore the design space of providing downlink connectivity to BLE-only devices, give an overview of the challenges, and propose a system to enable downlink BLE communication.

Heavy metal contamination in soil presents substantial risks to public health, industry, and the larger biosphere. Current methodologies for detecting heavy elements rely on labor-intensive sampling methods and time-consuming laboratory analysis, limiting temporal and spatial resolution. We present HERMES, an in-development heavy metal monitoring system that can be placed around high risk areas. HERMES leverages soil microbial fuel cells as autonomous biosensors. These biosensors when deployed as a sensor field, can monitor soil conditions and transmit data using a distributed machine learning framework. By providing improvements in the speed and resolution of heavy metal contamination detection, HERMES aims to enable earlier intervention and mitigate long-term damages.

We present a case study formally verifying process isolation in the Tock production microcontroller OS kernel. Tock combines hardware memory protection units and language-level techniques—by writing the kernel in Rust—to enforce isolation between user and kernel code. Our effort to verify Tock's process abstraction unearthed multiple, subtle bugs that broke isolation—many allowing malicious applications to compromise the whole OS. We describe this effort and TickTock, our fork of the Tock operating system kernel that eliminates isolation bugs by construction. TickTock uses Flux, an SMT-based Rust verifier, to formally specify and verify process isolation for all ARMv7-M platforms Tock supports and for three RISC-V 32-bit platforms. Our verification-guided design and implementation led to a new, granular process abstraction that is simpler than Tock's, has formal security guarantees (that are verified in half a minute), and outperforms Tock on certain critical code paths.

Today's computational devices are overwhelmingly wireless. To realize wireless communication, today's devices use a grab bag of protocols (Bluetooth, WiFi, 4G/5G, LoRa, NFC, etc.) and no one universal standard has emerged. This diversity presents a ripe pedagogical opportunity to introduce students to the fundamental tradeoffs and design decisions inherent to wireless communication and networking. Furthermore, many wireless protocols are accessible to study in a classroom (in fact, many we all use daily), which lends to a very hands-on course.

1.5 billion smartphones are sold annually, and most are decommissioned less than two years later. Most of these unwanted smartphones are neither discarded nor recycled but languish in junk drawers and storage units. This computational stockpile represents a substantial wasted potential: modern smartphones have increasingly high-performance and energy-efficient processors, extensive networking capabilities, and a reliable built-in power supply. This project studies the ability to reuse smartphones as "junkyard computers." Junkyard computers grow global computing capacity by extending device lifetimes, which supplants the manufacture of new devices. We show that the capabilities of even decade-old smartphones are within those demanded by modern cloud microservices and discuss how to combine phones to perform increasingly complex tasks. We describe how current operation-focused metrics do not capture the actual carbon costs of compute. We propose Computational Carbon Intensity---a performance metric that balances the continued service of older devices with the superlinear runtime improvements of newer machines. We use this metric to redefine device service lifetime in terms of carbon efficiency. We develop a cloudlet of reused Pixel 3A phones. We analyze the carbon benefits of deploying large, end-to-end microservice-based applications on these smartphones. Finally, we describe system architectures and associated challenges to scale to cloudlets with hundreds and thousands of smartphones.

This paper discusses experiments on soil-based microbial fuel cells (MFCs) as energy scavenging sources. We explain the mechanism of operation for MFCs, perform controlled laboratory experiments of MFCs, and deploy a small-scale insitu pilot in an active farm. We find that traditional energy harvester ICs draw power too aggressively, which reduces overall energy capture. We show that isolated MFCs can be combined in series or parallel to improve the voltage or current output of the harvesting source. Lastly, we observe that under a real-world, drip-irrigated agricultural setting, MFC output is appreciably lower, but consistent at 0.5-2 microwatts.

We demonstrate how to leverage Apple's Find My protocol, most well known as the underlying protocol of the AirTag, for arbitrary data-muling. This provides a new "infrastructure-free" deployment option, where areas with frequent human activity can take advantage of this zero-cost backhaul network. While there are severe limitations (e.g. no acknowledgement channel back to the sending device), Find My-based networking could still be a highly reliable backhaul with sufficient transmission redundancy and knowledge of deployment context.

Soil microbial fuel cells are a promising source of energy for outdoor sensor networks. These biological systems are sensitive to environmental conditions, therefore more data is needed on their behavior "in the wild" to enable the creation of an energy system capable of being widely deployed. Prior work on early characterization of microbial fuel cells relied on extremely accurate, but expensive, logging hardware. To scale up the number of deployment sites, we present custom logging hardware, specially designed to accurately monitor the behavior of microbial fuel cells at low cost. This paper describes the design and evaluation of the board, which is open source and freely available on GitHub.

On average, wireless electronics devices are replaced every 50 months. On average, a bridge is replaced every 50 years. As we begin to imagine integrating electronics and intelligence into the built environment, we need to to begin to think about electronic devices and systems on infrastructure timelines. This is not to say that every individual electronic device can, will, or should last for decades, but much like the ship of Theseus, the system that defines emerging Smart Cities will have a lifetime reaching into the century-scale. In this paper, we contemplate what the devices, gateways, network architectures, and their management might look like for a system designed to operate for decades. The result is a mixture of actionable insights for today and research questions for tomorrow, which culminates in the commencement of a 50-year experiment designed to see how long energy-harvesting sensors, without the implicit lifetime of batteries, can remain viable without human attention or intervention.

In this paper, we provide the first broad measurement study of the operation, adoption, performance, and efficacy of Helium. The Helium network aims to provide low-power, wide-area network wireless coverage for Internet of Things-class devices. In contrast to traditional infrastructure, "hotspots" (base stations) are owned and operated by individuals who are paid by the network for providing coverage and are paid directly by users for ferrying data.

This demo showcases the power delivery potential of soil-based microbial fuel cells. We build a prototype energy harvesting setup for a soil microbial fuel cell, measure the amount of power that we can harvest, and use that energy to drive an e-ink display. Microbial fuel cells are highly sensitive to environmental conditions, especially soil moisture. In near-optimal, super moist conditions our cell provides approximately 100 μW of power at around 500 mV, which is ample power over time to power our system several times a day. In sum, we find that the confluence of ever lower-power electronics and new understanding of microbial fuel cell design means that "soil-powered sensors" are now feasible. There remains, however, significant future work to make these systems reliable and maximally performant.

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 2000 mAh battery. Finally, to validate its deployability and efficacy, SociTrack is used by early childhood development researchers to capture caregiver-infant interactions.

The Internet of Things (IoT) is a rapidly evolving application space. One of the fascinating new fields in IoT research is mm-scale sensors, which make up the Internet of Tiny Things (IoT2). With their miniature size, these systems are poised to open up a myriad of new application domains. Enabled by the unique characteristics of cyber-physical systems and recent advances in low-power design and bare-die 3D chip stacking, mm-scale sensors are rapidly becoming a reality. In this paper, we will survey the challenges and solutions to 3D-stacked mm-scale design, highlighting low-power circuit issues ranging from low-power SRAM and miniature neural network accelerators to radio communication protocols and analog interfaces. We will discuss system-level challenges and illustrate several complete systems and their merging application spaces.

The vision of sensor systems that collect critical and previously ungathered information about the world is often only realized when sensors, students, and subjects move outside the academic laboratory. However, deployments at even the smallest scales introduce complexities and risks that can be difficult for a research team to anticipate. Over the past year, our interdisciplinary team of engineers and economists has been designing, deploying, and operating a large sensor network in Accra, Ghana that measures power outages and quality at households and firms. This network consists of 457 custom sensors, over 3,000 mobile app instances, thousands of participant surveys, and custom user incentive and deployment management systems. In part, this deployment supports an evaluation of the impacts of investments in the grid on reliability and the subsequent effects of improvements in reliability on socioeconomic well-being. We report our experiences as we move from performing small pilot deployments to our current scale, attempting to identify the pain points at each stage of the deployment. Finally, we extract high-level observations and lessons learned from our deployment activities, which we wish we had originally known when forecasting budgets, human resources, and project timelines. These insights will be critical as we look toward scaling our deployment to the entire city of Accra and beyond, and we hope that they will encourage and support other researchers looking to measure highly granular information about our world's critical systems.

Incentives are a key facet of human studies research, yet the state-of-the-art often designs and implements incentive systems in an ad-hoc, on-demand manner. We introduce the first vocabulary for formally describing incentive systems and develop a software infrastructure that enables UI-based graphical generation of complex, auditable, reliable, and reproducible incentive systems. We call this infrastructure the Open INcentive Kit (OINK). A review of recent literature from several communities finds that of the one hundred and twenty-one publications that incorporate incentives, only thirty-one describe their incentive system in detail, and all of these could be implemented using OINK. We evaluate OINK in practice by using it for an active energy monitoring deployment in Ghana and find that OINK successfully facilitates thousands of individual incentive payments. Finally, we describe our efforts to generalize OINK for different research communities, specifically focusing on architectural decisions around extensibility to support unanticipated use cases. OINK is free and open-source software.

We present TotTernary, the first infrastructure-free, long-term research platform which enables domain scientists to measure human interactions with previously unprecedented accuracy and flexibility. The platform can be tailored to varying scenarios by adjusting the ranging fidelity and the update rate and demonstrates dynamic adaptation to its environment. As a mobile, accurate, and reliable system for ranging measurements, it allows users to gather both distance and position information with decimeter accuracy. Measuring only 61 X 35 mm and weighing 7.7 g, it integrates two radios to achieve both low-power neighbour discovery and direct user interactions using Bluetooth Low Energy as well as precise ultra-wideband ranging measurements. The system introduces a novel energy-efficient ranging protocol with linear message complexity to achieve life times of up to 39 days. Furthermore, leveraging both antenna and frequency diversity, we demonstrate that the median ranging error can be reduced by up to 86% through an efficient aggregation of measurements over multiple channels. Our system is capable of highly reliable and consistent measurements with as little as 14.8 cm of ranging error in the 99th percentile and a 90% confidence interval of 11.3 cm.

City-scale sensing holds the promise of enabling deeper insight into how our urban environments function. Applications such as observing air quality and measuring traffic flows can have powerful impacts, allowing city planners and citizen scientists alike to understand and improve their world. However, the path from conceiving applications to implementing them is fraught with difficulty. A successful city-scale deployment requires physical installation, power management, and communications-all challenging tasks standing between a good idea and a realized one. The Signpost platform, presented at IPSN 2018, has been created to address these challenges. Signpost enables easy deployment by relying on harvested, solar energy and wireless networking rather than their wired counterparts. To further lower the bar to deploying applications, the platform provides the key resources necessary to support its pluggable sensor modules in their distributed sensing tasks. In this demo, we present the Signpost hardware and several applications running on a deployment of Signposts on UC Berkeley's campus, including distributed, energy-adaptive traffic monitoring and fine grained weather reporting. Additionally we show the cloud infrastructure supporting the Signpost deployment, specifically the ability to push new applications and parameters down to existing sensors, with the goal of demonstrating that the existing deployment can serve as a future testbed.

City-scale sensing holds the promise of enabling a deeper understanding of our urban environments. However, a city-scale deployment requires physical installation, power management, and communications all challenging tasks standing between a good idea and a realized one. This indicates the need for a platform that enables easy deployment and experimentation for applications operating at city scale. To address these challenges, we present Signpost, a modular, energy-harvesting platform for city-scale sensing. Signpost simplifies deployment by eliminating the need for connection to wired infrastructure and instead harvesting energy from an integrated solar panel. The platform furnishes the key resources necessary to support multiple, pluggable sensor modules while providing fair, safe, and reliable sharing in the face of dynamic energy constraints. We deploy Signpost with several sensor modules, showing the viability of an energy-harvesting, multi-tenant, sensing system, and evaluate its ability to support sensing applications. We believe Signpost reduces the difficulty inherent in city-scale deployments, enables new experimentation, and provides improved insights into urban health.

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.

Network connectivity is often one of the most challenging aspects of deploying sensors. In many countries, cellular networks provide the most reliable, highest bandwidth, and greatest coverage option for internet access. Repurposing smartphones as gateways could extract value from hundreds of millions of devices currently considered to be e-waste. While these factors make smartphones a seemingly ideal platform to serve as a gateway between sensors and the cloud, we find that a device designed for multi-tenant operation and frequent human interaction becomes unreliable when tasked to continuously run a single application with no human interaction, a somewhat counter-intuitive result. Further, we find that economy phones cannot physically withstand continuous operation, resulting in a surprisingly high rate of permanent device failures in the field. If these observations hold more broadly, they would make mobile phones poorly suited to a range of sensing applications for which they have been rumored to hold great promise.

Network connectivity is often one of the most challenging aspects of deploying sensors. In many countries, cellular networks provide the most reliable, highest bandwidth, and greatest coverage option for Internet access. While this makes smartphones a seemingly ideal platform to serve as a gateway between sensors and the cloud, we find that a device designed for multi-tenant operation and frequent human interaction becomes unreliable when tasked to continuously run a single application with no human interaction, a seemingly counter-intuitive result. Further, we find that economy phones cannot physically withstand continuous operation, resulting in a surprisingly high rate of permanent device failures in the field. If these observations hold more broadly, they would make mobile phones poorly suited to a range of sensing applications for which they have been rumored to hold great promise.

We introduce Harmonium , a novel ultra wideband (UWB) RF localization architecture that achieves decimeter-scale accuracy indoors. Harmonium strikes a balance between tag simplicity and processing complexity to provide fast and accurate indoor location estimates. Harmonium uses only commodity components and consists of a small, inexpensive, lightweight, and FCC-compliant UWB transmitter or tag , fixed infrastructure anchors with known locations, and centralized processing that calculates the tag’s position. Anchors employ a new frequency-stepped narrowband receiver architecture that rejects narrowband interferers and extracts high-resolution timing information without the cost or complexity of traditional UWB approaches. In a complex indoor environment, 90% of position estimates obtained with Harmonium exhibit less than 31 cm of error with an average of 9 cm of inter-sample noise. In non-line-of-sight conditions (i.e., through-wall), 90% of position error is less than 42 cm. The tag draws 75 mW when actively transmitting, or 3.9 mJ per location fix at the 19 Hz update rate. Tags weigh 3 g and cost $4.50 USD at modest volumes. Furthermore, VLSI-based design concepts are identified for a simple, low-power realization of the Harmonium tag to offer a roadmap for the realization of Harmonium concepts in future integrated systems. Harmonium introduces a new design point for indoor localization and enables localization of small, fast objects such as micro quadrotors, devices previously restricted to expensive optical motion capture systems.

City-scale sensing holds the promise of enabling deeper insight into how our urban environments function. Applications such as observing air quality and measuring sources of noise pollution can have powerful impacts, allowing city planners and citizen scientists alike to understand and improve their world. However, the path from conceiving applications to implementing them is fraught with many challenges. A successful city-scale deployment requires physical installation, power management, and communications---all challenging tasks standing between a good idea and a realized one, suggesting the need for a platform that enables easy deployment and experimentation of city-scale sensing applications. To address these basic challenges, we present Signpost, a modular platform for city-scale sensing. Signpost simplifies deployment and installation in cities by removing the need for connection to wired infrastructure and instead harvesting energy from an integrated solar panel. The platform provides the key resources necessary for its pluggable sensor modules to support city-scale applications. Signpost stores excess energy for later use, distributes energy between modules, and provides communication through multiple wireless protocols. It also offers local storage for sensor data and allows for additional processing in a duty-cycled Linux environment.

Low-power microcontrollers lack some of the hardware features and most of the memory resources that usually enable multiprogrammable systems. Accordingly, operating system software for these platforms has not provided important features like memory isolation, dynamic memory allocation, and flexible concurrency. However, an emerging class of embedded applications are software platforms, rather than single purpose devices. Tock, a new operating system for low-power platforms, takes advantage of the limited hardware-protection mechanisms available on recent microcontrollers and the type-safety features of the Rust programming language to provide a multiprogramming environment that offers isolation of software faults, memory protection, and efficient memory management for dynamic application workloads written in any language while retaining the dependability requirements of long-running devices.

Low-power microcontrollers lack some of the hardware features and memory resources that enable multiprogrammable systems. Accordingly, microcontroller-based operating systems have not provided important features like fault isolation, dynamic memory allocation, and flexible concurrency. However, an emerging class of embedded applications are software platforms, rather than single purpose devices, and need these multiprogramming features. Tock, a new operating system for low-power platforms, takes advantage of limited hardware-protection mechanisms as well as the type-safety features of the Rust programming language to provide a multiprogramming environment for microcontrollers. Tock isolates software faults, provides memory protection, and efficiently manages memory for dynamic application workloads written in any language. It achieves this while retaining the dependability requirements of long-running applications.

We introduce Harmonium, a novel ultra-wideband RF localization architecture that achieves decimeter-scale accuracy indoors. Harmonium strikes a balance between tag simplicity and processing complexity to provide fast and accurate indoor location estimates. Harmonium uses only commodity components and consists of a small, inexpensive, lightweight, and FCC-compliant ultra-wideband transmitter or tag, fixed infrastructure anchors with known locations, and centralized processing that calculates the tag's position. Anchors employ a new frequency-stepped narrowband receiver architecture that rejects narrowband interferers and extracts high-resolution timing information without the cost or complexity of traditional ultra-wideband approaches. In a complex indoor environment, 90% of position estimates obtained with Harmonium exhibit less than 31 cm of error with an average 9 cm of inter-sample noise. In non-line-of-sight conditions (i.e. through-wall), 90% of position error is less than 42 cm. The tag draws 75 mW when actively transmitting, or 3.9 mJ per location fix at the 19 Hz update rate. Tags weigh 3 g and cost $4.50 USD at modest volumes. Harmonium introduces a new design point for indoor localization and enables localization of small, fast objects such as micro quadrotors, devices previously restricted to expensive optical motion capture systems.

The era of city-scale sensing is dawning. Supported by new sensing capabilities, the capability to detect and measure phenomena throughout a large area will allow deeper insight and understanding into how cities work. The challenge of city-scale sensing is not limited to developing new sensing applications, however. A sensor must be installed in a location. It must be provided power, storage, and communications. All these tasks stand aside from the desired sensing effort, but are necessary nevertheless.

We present SurePoint, a system for drop-in, high-fidelity indoor localization. SurePoint builds on recently available commercial ultra-wideband radio hardware. While ultra-wideband radio hardware can provide the timing primitives necessary for a simple adaptation of two-way ranging, we show that with the addition of frequency and spatial diversity, we can achieve a 53% decrease in median ranging error. Because this extra diversity requires many additional packets for each range estimate, we next develop an efficient broadcast ranging protocol for localization that ameliorates this overhead. We evaluate the performance of this ranging protocol in stationary and fast-moving environments and find that it achieves up to 0.08 m median error and 0.53 m 99th percentile error. As ranging requires the tag to have exclusive access to the channel, we next develop a protocol to coordinate the localization of multiple tags in space. This protocol builds on recent work exploiting the constructive interference phenomenon. The ultra-wideband PHY uses a different modulation scheme compared to the narrowband PHY used by previous work, thus we first explore the viability and performance of constructive interference with ultra-wideband radios. Finally, as the ranging protocol requires careful management of the ultra-wideband radio and tight timing, we develop TriPoint, a dedicated "drop-in" ranging module that provides a simple I2C interface. We show that this additional microcontroller demands only marginal energy overhead while facilitating interoperability by freeing the primary microcontroller to handle other tasks.

We present SurePoint, a system for drop-in, high-fidelity indoor localization. SurePoint builds on recently available commercial ultra-wideband radio hardware. While ultra-wideband radios provide a pairwise range estimate natively, we show that with the addition of frequency and spatial diversity, we can achieve a 53% decrease in median range error. Because this extra diversity requires many additional packets for each range estimate, we leverage an efficient broadcast ranging protocol for localization that ameliorates this overhead. In stationary and fast-moving environments SurePoint achieves up to 0.08 m median error and 0.53 m 99th percentile error. As ranging requires the tag to have exclusive access to the channel, we employ a protocol to coordinate the localization of multiple tags in space. This protocol builds on recent work exploiting the constructive interference phenomenon, however SurePoint is the first to demonstrate constructive interface using the 802.15.4a ultra-wideband PHY. Finally, as the ranging protocol requires careful management of the ultra-wideband radio and tight timing, we utilize TriPoint, a dedicated "drop-in" ranging module that provides a simple I2C interface. We show that this additional microcontroller demands only marginal energy overhead while facilitating interoperability by freeing the primary microcontroller to handle other tasks.

For the last fifteen years, research explored the hardware, software, sensing, communication abstractions, languages, and protocols that could make networks of small, embedded devices---motes---sample and report data for long periods of time while unattended. Today, the application and technological landscapes have shifted, introducing new requirements and new capabilities. Hardware has evolved past 8 and 16 bit microcontrollers: there are now 32 bit processors with lower energy budgets and greater computing capability. New wireless link layers have emerged, creating protocols that support direct interaction with users, but introduce novel limitations that systems must consider. Programming language advances have led to the ability to write system kernels that guarantee safety and reliability while maintaining low overhead. The time has come to look beyond optimizing networks of motes. We look towards new technologies such as Bluetooth Low Energy, Cortex M processors, and capable multi-process operating systems, with new application spaces such as personal area networks, and new capabilities and requirements in security and privacy to inform contemporary hardware and software platforms. It is time for a new, open experimental platform in this post-mote era.

As we show in this paper, I/O has become the limiting factor in scaling down size and power toward the goal of invisible computing. Achieving this goal will require composing optimized and specialized---yet reusable---components with an interconnect that permits tiny, ultra-low power systems. In contrast to today's interconnects which are limited by power-hungry pull-ups or high-overhead chip-select lines, our approach provides a superset of common bus features but at lower power, with fixed area and pin count, using fully synthesizable logic, and with surprisingly low protocol overhead.

Building connected, pervasive, human-facing, and responsive applications that incorporate local sensors, smartphone interactions, device actuation, and cloud-based learning--the promised features of the Internet of Things (IoT)---requires a complete suite of tools spanning both hardware and software. We present a set of these pieces, including a gateway, four hardware building blocks, multiple sensor platforms, an indoor localization system, and software for connecting users and devices. Each piece plays an integral role towards enabling applications, from facilitating rapid development of wireless smart devices to composing data streams and services from a diverse set of components. By providing layered interoperable systems, our toolkit offers cohesive support for moving beyond single-device, cloud-centric applications---typical in today's IoT landscape--and towards richer applications that incorporate multiple data streams, human interaction, cloud processing, location awareness, multiple communication protocols, historical data, access control, and on-demand user interfaces. To show how the pieces in the toolkit cooperate, we demonstrate a location-based access control application where a user's smartphone can control a room's lighting, but only from within the room. Further, data streams from the phone and nearby sensors are used to provide a constant lighting service which attempts to maintain a user-set brightness under variable external lighting conditions.

We demonstrate PolyPoint, a high-fidelity RF-based indoor localization system that achieves 28~cm accuracy indoors and tracks a fast-moving quadcopter with only 56~cm average error. PolyPoint uses ultra-wideband signals to achieve high precision RF time-of-flight estimates between nodes. To further improve accuracy, PolyPoint exploits two forms of diversity: frequency diversity, which leverages several ultra-wideband channels to improve channel response, and antenna diversity, which adds three antennas at 120 degree offsets to mitigate the effects of antenna polarization and nulls. PolyPoint introduces an efficient, novel ranging protocol that maximizes these diversity sources with a minimal number of packets.

Rust, a new systems programming language, provides compile-time memory safety checks to help eliminate runtime bugs that manifest from improper memory management. This feature is advantageous for operating system development, and especially for embedded OS development, where recovery and debugging are particularly challenging. However, embedded platforms are highly event-based, and Rust's memory safety mechanisms largely presume threads. In our experience developing an operating system for embedded systems in Rust, we have found that Rust's ownership model prevents otherwise safe resource sharing common in the embedded domain, conflicts with the reality of hardware resources, and hinders using closures for programming asynchronously. We describe these experiences and how they relate to memory safety as well as illustrate our workarounds that preserve the safety guarantees to the largest extent possible. In addition, we draw from our experience to propose a new language extension to Rust that would enable it to provide better memory safety tools for event-driven platforms.

We explore the indoor positioning problem with unmodified smartphones and slightly-modified commercial LED luminaires. The luminaires - modified to allow rapid, on-off keying - transmit their identifiers and/or locations encoded in human-imperceptible optical pulses. A camera-equipped smartphone, using just a single image frame capture, can detect the presence of the luminaires in the image, decode their transmitted identifiers and/or locations, and determine the smartphone's location and orientation relative to the luminaires. Continuous image capture and processing enables continuous position updates. The key insights underlying this work are (i) the driver circuits of emerging LED lighting systems can be easily modified to transmit data through on-off keying; (ii) the rolling shutter effect of CMOS imagers can be leveraged to receive many bits of data encoded in the optical transmissions with just a single frame capture, (iii) a camera is intrinsically an angle-of-arrival sensor, so the projection of multiple nearby light sources with known positions onto a camera's image plane can be framed as an instance of a sufficiently-constrained angle-of-arrival localization problem, and (iv) this problem can be solved with optimization techniques.

We explore the indoor positioning problem with unmodified smartphones and slightly-modified commercial LED luminaires. The luminaires-modified to allow rapid, on-off keying-transmit their identifiers and/or locations encoded in human-imperceptible optical pulses. A camera-equipped smartphone, using just a single image frame capture, can detect the presence of the luminaires in the image, decode their transmitted identifiers and/or locations, and determine the smartphone's location and orientation relative to the luminaires. Continuous image capture and processing enables continuous position updates. The key insights underlying this work are (i) the driver circuits of emerging LED lighting systems can be easily modified to transmit data through on-off keying; (ii) the rolling shutter effect of CMOS imagers can be leveraged to receive many bits of data encoded in the optical transmissions with just a single frame capture, (iii) a camera is intrinsically an angle-of-arrival sensor, so the projection of multiple nearby light sources with known positions onto a camera's image plane can be framed as an instance of a sufficiently-constrained angle-of-arrival localization problem, and (iv) this problem can be solved with optimization techniques. We explore the feasibility of the design through an analytical model, demonstrate the viability of the design through a prototype system, discuss the challenges to a practical deployment including usability and scalability, and demonstrate decimeter-level accuracy in both carefully controlled and more realistic human mobility scenarios.

Currently, researchers study face-to-face interactions using wearable sensors and smartphones which provide 2 to 5 m proximity sensing every 20 to 300 s. However, studying interaction distance, which is known to impact disease spread, communication behavior, and other phenomenon, has proven challenging. Smartphones are limited by their inaccurate and/or impractical ranging capabilities, while wearable sensors are limited by their need for infrastructure nodes, bulkiness, and/or inaccurate ranging. To address these challenges, we present Opo, a 14 cm2, 11.4 g "lapel pin" built from commercial components. Opo sensors range neighbors every 2 s up to 2 m away with 5% average error, all while requiring zero infrastructure and improving upon current wearable sensors' accuracy and power usage. The cornerstone of Opo is an ultrasonic wakeup circuit that draws 19 μA when no neighbors are present. This enables Opo sensors to discover and range neighbors without the need for infrastructure nodes and slow or power-hungry RF discovery protocols. Thus, Opo is able to sense interaction distance with high accuracy (5 cm) and temporal fidelity (2 s) on a limited power budget.

For the last fifteen years, research explored the hardware, software, sensing, communication abstractions, languages, and protocols that could make networks of small, embedded devices---motes---sample and report data for long periods of time unattended. Today, the application and technological landscapes have shifted, introducing new requirements and new capabilities. Hardware has evolved past 8 and 16 bit microcontrollers: there are now 32 bit processors with lower energy budgets and greater computing capability. New wireless link layers have emerged, creating protocols that support rapid and efficient setup and teardown but introduce novel limitations that systems must consider. The time has come to look beyond optimizing networks of motes. We look towards new technologies such as Bluetooth Low Energy, Cortex M processors, and capable energy harvesting, with new application spaces such as personal area networks, and new capabilities and requirements in security and privacy to inform contemporary hardware and software platforms. It is time for a new, open experimental platform in this post-mote era.

Packet collisions have gone from something to be avoided to something that can be embraced. We build upon recent results that employ intentional packet collisions for synchronized flooding to show how multi-hop wireless networks can support real-time actuation and control. First, we show how a network of nodes can synchronize their LED transmissions to extend the range of a visual light communication (VLC) system. Second, we show how buffer-free, streaming audio is possible over a multi-hop wireless mesh network.

In this work we expose the challenges of interfacing both conventional and new systems with an extremely resource constrained platform. We find that even when attempts are made to utilize an industry standard protocol (I2C), necessary protocol modifications for ultra-low power design means that interfacing remains non-trivial.

Most modern software-defined radios are large, expensive, and power-hungry, and this diminishes their utility in low-power, size-constrained settings like sensor networks and mobile computing. We explore the viability of scaling down the software radio in size, cost, and power, and show that an index card-sized, sub-$150, 'AA' battery-powered system is possible using off-the-shelf components. Key to our approach is that we leverage an integrated, reconfigurable, flash-based FPGA with a hard ARM Cortex-M3 microprocessor which simultaneously enables lower power and tighter hardware/software integration than prior designs. This architecture allows us to implement timing-critical MAC protocols and validate the speculated performance of several recent MAC/PHY primitives and protocols including Backcast, A-MAC, and Glossy using an IEEE 802.15.4-compliant radio implementation that interoperates with commercial radios. The work also identifies several enhancements in the underlying hardware components that could improve power, performance, and flexibility.