IoT devices rely on environment detection to trigger specific actions, e.g., for headphones to adapt noise cancellation to the surroundings. While phones feature many sensors, from GNSS to cameras, small wearables must rely on the few energy-efficient components they already incorporate. In this paper, we demonstrate that a Bluetooth radio is the only component required to accurately classify environments and present BlueSeer, an environment-detection system that solely relies on received BLE packets and an embedded neural network. BlueSeer achieves an accuracy of up to 84% differentiating between 7 environments on resource-constrained devices, and requires only ~ 12 ms for inference on a 64 MHz microcontroller-unit.

Testbeds have become a vital tool for evaluating and benchmarking applications and algorithms in the Internet of Things (IoT). Testbeds commonly consist of low-power IoT de-vices augmented with observer nodes providing control, logging, and often also power-profiling. Today, the research community operates numerous testbeds, sometimes with hundreds of IoT nodes, to allow for detailed and large-scale evaluation. Most testbeds, however, lack opportunities for tracing distributed program execution with high accuracy in time, for example, via minimally invasive, distributed GPIO tracing. And the ones that do, like Flocklab, are built from custom hardware, which is often too complex, inflexible, or expensive to use for other research groups.This paper closes this gap and introduces Grace, a low-cost, retrofittable, distributed, and time-synchronized GPIO tracing system built from off-the-shelf components, costing less than €20 per node. Grace extends observer nodes in a testbed with (1) time-synchronization via wireless sub-GHz transceivers and (2) logic analyzers for GPIO tracing and logging, enabling time-synchronized GPIO tracing at a frequency of up to 8 MHz. We deploy Grace in a testbed and show that it achieves an average time synchronization error between nodes of 1.53 μs.

Low-power wireless networking commonly uses either Time-Slotted Channel Hopping (TSCH), synchronous transmissions, or opportunistic routing. All three of these different, orthogonal approaches strive for efficient and reliable communication but follow different trajectories. With this paper, we combine these concepts into one protocol: Autobahn.Autobahn merges TSCH scheduling with opportunistically routed, synchronous transmissions. This opens the possibility to create long-term stable schedules overcoming local interference. We prove the stability of schedules over several days in our experimental evaluation. Moreover, Autobahn outperforms the autonomous scheduler Orchestra under interference in terms of reliability by 13.9 percentage points and in terms of latency by a factor of 9 under a minor duty cycle increase of 2.1 percentage points.

Wireless Sensor-Actuator Networks (WSANs) are an important driver for the Industrial Internet of Things (IIoT) as they easily retrofit existing industrial infrastructure. Industrial applications require these networks to provide stable communication with high reliability and guaranteed low latency. A common way is using a central scheduler to plan transmissions and routes so that all packets are delivered before a deadline. However, existing centralized schedulers are only able to achieve high reliability in the absence of interference. This limitation lowers the feasibility of using centralized schedulers in most environments susceptible to interference.This paper addresses the challenge of stable, centrally scheduled communication in low-power wireless networks susceptible to interference. We introduce MASTER, a centralized scheduler and router, for IEEE 802.15.4 TSCH (Time-Slotted Channel Hopping). MASTER uses Sliding Windows, a novel transmission strategy, which builds on flow-based retransmissions instead of link-based ones. We show in our experimental evaluation that MASTER with Sliding Windows achieves routing and scheduling stability for over 24 hours with end-to-end reliability of over 99.6%. Moreover, we show that MASTER outperforms Orchestra, a state-of-the-art autonomous scheduler, in terms of latency by a factor of 8 while achieving similar reliability under a slight duty-cycle increase.

In this paper, we present Overtake, an opportunistic routing protocol for Time-Slotted Channel Hopping (TSCH). Overtake combines (1) opportunistic routing, (2) concurrent transmissions and (3) TSCH. We show that this novel combination enables low-latency, central scheduling withstanding node failures. Our initial results show its ability to withstand node failures of up to 40% of nodes of a flow while keeping minimal latency.

There is the long-standing assumption that radio communication in the range of hundreds of meters needs to consume mWs of power at the transmitting device. In this paper, we demonstrate that this is not necessarily the case for some devices equipped with backscatter radios. We present LOREA an architecture consisting of a tag, a reader and multiple carrier generators that overcomes the power, cost and range limitations of existing systems such as Computational Radio Frequency Identification (CRFID). LOREA achieves this by: First, generating narrow-band backscatter transmissions that improve receiver sensitivity. Second, mitigating self-interference without the complex designs employed on RFID readers by keeping carrier signal and backscattered signal apart in frequency. Finally, decoupling carrier generation from the reader and using devices such as WiFi routers and sensor nodes as a source of the carrier signal. An off-the-shelf implementation of LOREA costs 70 USD, a drastic reduction in price considering commercial RFID readers cost 2000 USD. LOREA's range scales with the carrier strength, and proximity to the carrier source and achieves a maximum range of 3.4 km when the tag is located at 1 m distance from a 28 dBm carrier source while consuming 70 μW at the tag. When the tag is equidistant from the carrier source and the receiver, we can communicate upto 75 m, a significant improvement over existing RFID readers.