Publications

Abstract not provided.

Internet of Things (IoT) devices rely upon remote firmware updates to fix bugs, update embedded algorithms, and make security enhancements. Remote firmware updates are a significant burden to wireless IoT devices that operate using low-power wide-area network (LPWAN) technologies due to slow data rates. One LPWAN technology, Long Range (LoRa), has the ability to increase the data rate at the expense of range and noise immunity. The optimization of communications for maximum speed is known as adaptive data rate (ADR) techniques, which can be applied to accelerate the firmware update process for any LoRa-enabled IoT device. In this paper, we investigate ADR techniques in an application that provides remote monitoring of cattle using small, battery-powered devices that transmit data on cattle location and health using LoRa. In addition to issues related to firmware update speed, there are significant concerns regarding reliability and security when updating firmware on mobile, energy-constrained devices. A malicious actor could attempt to steal the firmware to gain access to embedded algorithms or enable faulty behavior by injecting their own code into the device. A firmware update could be subverted due to cattle moving out of the LPWAN range or the device battery not being sufficiently charged to complete the update process. To address these concerns, we propose a secure and reliable firmware update process using ADR techniques that is applicable to any mobile or energy-constrained LoRa device. The proposed system is simulated and then implemented to evaluate its performance and security properties.

Long Range (LoRa) is an emerging low-power wide-area network technology. LoRa messages can be transmitted with a variety of parameters including transmit power, spreading factor, bandwidth, and error coding rates. While adaptive data rate (ADR) capabilities exist in the LoRa wide-area network (LoRaWAN) specification, this work is motivated by a cattle monitoring application where LoRaWAN is not feasible. In this scenario, the mobility of the animal changes the optimal parameter selections, which are the settings that transmit the data with the lowest energy consumption. This work analyzes ADR techniques to most efficiently find the optimal data rate for a firmware update, although the techniques are still valid for any large data exchange. It extends the ADR to use frequency shift keying (FSK) when there is enough signal strength since Semtech LoRa integrated circuits support FSK mode. The work uses dynamic acknowledgements and timeout values to improve the convergence time. The paper experimentally validates an analytical transmit time model and then describes three different methods for accomplishing the adaptive data rate. The methods are modeled analytically for the different convergence settings and two are demonstrated using the Microchip SAMR34 Explained boards.

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This report details work at Sandia National Laboratories in development of a lithium-ion battery management system (BMS) designed to detect the state of charge (SOC) and state of health (SOH) of a battery. The goal was to create a BMS that provides advanced SOH information without adding complexity to the hardware already required for monitoring battery safety. The hardware is designed to have low processor requirements and relatively low cost components, while offering several high end battery management options like communication, automatic SOC detection, capacity tracking, and multiple SOH characteristics. The methods for detecting capacity include coulomb counting and resistance-compensated voltage calculations. Several methods for assessing the SOH were also considered, including deviations in capacity using coulomb counting, DC resistance analysis, and time domain resistance analysis.

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