On Flashing Over The Air “FOTA” for IoT Appliances – An ATMEL Prototype

Badawy, W.; Ahmed, Ahmed I.; Sharf, Samy H.; Elhamied, Rafaat Abd; Mekky, Mostafa; Elhamied, Mohamed Abd

doi:10.1109/icce-berlin50680.2020.9352203

Cited by 14 publications

(5 citation statements)

References 8 publications

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“…The authors of [16] presented a system for remotely flashing ATMEL AVR microcontrollers via Wi-Fi and LoRa technologies. The paper was mainly focused on the hardware part, and not on the exchange of firmware chunks.…”

Section: Over the Air Update Of Iot Devicesmentioning

confidence: 99%

Firmware Updates over the Air via LoRa: Unicast and Broadcast Combination for Boosting Update Speed

Malumbres,

Saldana,

Berné

et al. 2024

Sensors

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The capacity to update firmware is a vital component in the lifecycle of Internet of Things (IoT) devices, even those with restricted hardware resources. This paper explores the best way to wirelessly (Over The Air, OTA) update low-end IoT nodes with difficult access, combining the use of unicast and broadcast communications. The devices under consideration correspond to a recent industrial IoT project that focuses on the installation of intelligent lighting systems within ATEX (potentially explosive atmospheres) zones, connected via LoRa to a gateway. As energy consumption is not limited in this use case, the main figure of merit is the total time required for updating a project. Therefore, the objective is to deliver all the fragments of the firmware to each and all the nodes in a safe way, in the least amount of time. Three different methods, combining unicast and broadcast transmissions in different ways, are explored analytically, with the aim of obtaining the expected update time. The methods are also tested via extensive simulations, modifying different parameters such as the size of the scenario, the number of bytes of each firmware chunk, the number of nodes, and the number of initial broadcast rounds. The simulations show that the update time of a project can be significant, considering the limitations posed by regulations, in terms of the percentage of airtime consumption. However, significant time reductions can be achieved by using the proper method: in some cases, when the number of nodes is high, the update time can be reduced by two orders of magnitude if the correct method is chosen. Moreover, one of the proposed methods is implemented using actual hardware. This real implementation is used to perform firmware update experiments in a lab environment. Overall, the article illustrates the advantage of broadcast approaches in this kind of technology, in which the transmission rate is constant despite the distance between the gateway and the node. However, the advantage of these broadcast methods with respect to the unicast one could be mitigated if the nodes do not run exactly the same firmware version, since the control of the broadcast update would be more difficult and the total update time would increase.

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Section: Over the Air Update Of Iot Devicesmentioning

confidence: 99%

Firmware Updates over the Air via LoRa: Unicast and Broadcast Combination for Boosting Update Speed

Malumbres,

Saldana,

Berné

et al. 2024

Sensors

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“…To further ensure that the devices are secure, regular firmware updates have to be provided. In the absence of easy physical access, it should be possible to provide remote firmware updates known as Firmware over the Air (FotA) [61]. Hence, the provision of FotA will become a key factor as well in choosing long-range technology.…”

Section: Lpwan Wireless Technologiesmentioning

confidence: 99%

Low-Power Wide-Area Networks: A Broad Overview of Its Different Aspects

et al. 2022

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Low-power wide-area networks (LPWANs) are gaining popularity in the research community due to their low power consumption, low cost, and wide geographical coverage. LPWAN technologies complement and outperform short-range and traditional cellular wireless technologies in a variety of applications, including smart city development, machine-to-machine (M2M) communications, healthcare, intelligent transportation, industrial applications, climate-smart agriculture, and asset tracking. This review paper discusses the design objectives and the methodologies used by LPWAN to provide extensive coverage for low-power devices. We also explore how the presented LPWAN architecture employs various topologies such as star and mesh. We examine many current and emerging LPWAN technologies, as well as their system architectures and standards, and evaluate their ability to meet each design objective. In addition, the possible coexistence of LPWAN with other technologies, combining the best attributes to provide an optimum solution is also explored and reported in the current overview. Following that, a comparison of various LPWAN technologies is performed and their market opportunities are also investigated. Furthermore, an analysis of various LPWAN use cases is performed, highlighting their benefits and drawbacks. This aids in the selection of the best LPWAN technology for various applications. Before concluding the work, the open research issues, and challenges in designing LPWAN are presented.INDEX TERMS Low-power wide-area networks, wireless networks, Internet of Things, design objectives, network topology, architecture, and applications. I. INTRODUCTIONThe Internet of Things (IoT) has the potential to change the way we live and work by providing its essential services to all the smart devices which are connected to it. IoT alleviates various challenges of wireless networks such as robust internet connectivity among a large population of smart devices, energy constraints in mobile edge devices, fast data transfer, efficient bandwidth utilization, and increased data gathering capability/reliability at the receiver. To achieve these goals, the devices must be optimally connected to the network, resulting in a fast exchange of sensed data facilitating intelligent decision-making to control the physical world phenomenon yielding a smart ecosystem. Several independent studies have predicted that in coming years IoT plays a crucial role in various social and commercial applications such as smart healthcare, intelligent transporta-tion, climate-smart agriculture, rescue operations, logistics, smart cities, industries, utilities, smart buildings, consumer electronics, security, asset tracking, smart waste management systems, cognitive manufacturing, and Machine-to-Machine (M2M) communications [1]-[5]. Furthermore, it has been estimated that by 2025, the adoption of smart M2M gadgets and electronic goods can overtake the number of human subscribers utilizing smartphones, desktops, notebooks, and similar objects. According to the analys...

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“…In [8], Badawy et al introduced Flashing Over The Air (FOTA) -a system to flash ATMEL AVR MCUs wirelessly. The said is achieved via Wifi and Long Range (LoRa) technology.…”

Section: 22mentioning

confidence: 99%

“…The volatility of the SRAM means that progress made in training a model will be erased when the MCU is reset or powered down. To mitigate the said issue, concepts from Flashing Over-the-Air [8] could be applied to ensure that progress is saved.…”

Section: Challengesmentioning

confidence: 99%

Intelligence at the Extreme Edge: A Survey on Reformable TinyML

Rajapakse¹,

Karunanayake²,

Nadeem³

2022

Preprint

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The rapid miniaturization of Machine Learning (ML) for low powered processing has opened gateways to provide cognition at the extreme edge (E.g., sensors and actuators). Dubbed Tiny Machine Learning (TinyML), this upsurging research field proposes to democratize the use of Machine Learning (ML) and Deep Learning (DL) on frugal Microcontroller Units (MCUs). MCUs are highly energy-efficient pervasive devices capable of operating with less than a few Milliwatts of power. Nevertheless, many solutions assume that TinyML can only run inference. Despite this, growing interest in TinyML has led to work that makes them reformable, i.e., work that permits TinyML to improve once deployed. In line with this, roadblocks in MCU based solutions in general, such as reduced physical access and long deployment periods of MCUs, deem reformable TinyML to play a significant part in more effective solutions. In this work, we present a survey on reformable TinyML solutions with the proposal of a novel taxonomy for ease of separation. Here, we also discuss the suitability of each hierarchical layer in the taxonomy for allowing reformability. In addition to these, we explore the workflow of TinyML and analyze the identified deployment schemes and the scarcely available benchmarking tools. Furthermore, we discuss how reformable TinyML can impact a few selected industrial areas and discuss the challenges and future directions.

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On Flashing Over The Air “FOTA” for IoT Appliances – An ATMEL Prototype

Cited by 14 publications

References 8 publications

Firmware Updates over the Air via LoRa: Unicast and Broadcast Combination for Boosting Update Speed

Firmware Updates over the Air via LoRa: Unicast and Broadcast Combination for Boosting Update Speed

Low-Power Wide-Area Networks: A Broad Overview of Its Different Aspects

Intelligence at the Extreme Edge: A Survey on Reformable TinyML

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