Revealing Characteristic IoT Behaviors by Performing Simple Energy Measurements via Open Hardware/Software Components

Loukatos, Dimitrios; Dimitriou, Nikos; Manolopoulos, Ioannis; Kontovasilis, Kimon; Arvanitis, Konstantinos G.

doi:10.1007/978-981-16-1781-2_90

Cited by 6 publications

(4 citation statements)

References 13 publications

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“…Future work on this topic includes the development of volume estimation system in scenarios of limited labeled data availability using unsupervised and semi-supervised learning. Moreover, use of more energy-efficient hardware, with hardware sleep- and activity-based wakeup, can be included to reduce the power consumption by this fluid intake monitoring system; thus, detailed characterization of energy consumption using the mechanisms mentioned in [ 26 ] can be explored.…”

Section: Discussionmentioning

confidence: 99%

An On-Device Learning System for Estimating Liquid Consumption from Consumer-Grade Water Bottles and Its Evaluation

Roy

Dutta

Griffith

et al. 2022

Sensors

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A lightweight on-device liquid consumption estimation system involving an energy-aware machine learning algorithm is developed in this work. This system consists of two separate on-device neural network models that carry out liquid consumption estimation with the result of two tasks: the detection of sip from gestures with which the bottle is handled by its user and the detection of first sips after a bottle refill. This predictive volume estimation framework incorporates a self-correction mechanism that can minimize the error after each bottle fill-up cycle, which makes the system robust to errors from the sip classification module. In this paper, a detailed characterization of sip detection is performed to understand the accuracy-complexity tradeoffs by developing and implementing a variety of different ML models with varying complexities. The maximum energy consumed by the entire framework is around 119 mJ during a maximum computation time of 300 μs. The energy consumption and computation times of the proposed framework is suitable for implementation in low-power embedded hardware that can be incorporated in consumer grade water bottles.

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Section: Discussionmentioning

confidence: 99%

An On-Device Learning System for Estimating Liquid Consumption from Consumer-Grade Water Bottles and Its Evaluation

Roy

Dutta

Griffith

et al. 2022

Sensors

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“…The purpose of taking multiple photos lays in the quality of the final combined image which will result by the unification of the different images and will be fed into the neural network at a next step (Section 2.2.2). The selected camera module is the ESP32-CAM, a compact, low-power OV2640 camera based on ESP32 that offers among else a resolution of 1600 × 1200 pixels, auto-focus and built-in Wi-Fi/Bluetooth modules (Figure 8a) [42] and is suitable for small-scale IoT solutions, in terms of cost, performance and energy consumption [43]. A plastic casing was designed and 3D printed aiming to protect it from external factors and mount it on the frame (Figure 8b).…”

Section: Sensors and Switchesmentioning

confidence: 99%

Design and Implementation of an Urban Farming Robot

2022

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Urban agriculture can be shortly defined as the growing of plants and/or the livestock husbandry in and around cities. Although it has been a common occupation for the urban population all along, recently there is a growing interest in it both from public bodies and researchers, as well as from ordinary citizens who want to engage in self-cultivation. The modern citizen, though, will hardly find the free time to grow his own vegetables as it is a process that requires, in addition to knowledge and disposition, consistency. Given the above considerations, the purpose of this work was to develop an economic robotic system for the automatic monitoring and management of an urban garden. The robotic system was designed and built entirely from scratch. It had to have suitable dimensions so that it could be placed in a balcony or a terrace, and be able to scout vegetables from planting to harvest and primarily conduct precision irrigation based on the growth stage of each plant. Fertigation and weed control will also follow. For its development, a number of technologies were combined, such as Cartesian robots’ motion, machine vision, deep learning for the identification and detection of plants, irrigation dosage and scheduling based on plants’ growth stage, and cloud storage. The complete process of software and hardware development to a robust robotic platform is described in detail in the respective sections. The experimental procedure was performed for lettuce plants, with the robotic system providing precise movement of its actuator and applying precision irrigation based on the specific needs of the plants.

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“…There are several areas that could benefit from open-source development that would reduce natural gas use for heating and some are already underway. Open hardware that is part of the internet of things (IOT) [119,120] is used for low-energy-consumption devices [121], monitoring power quality and energy savings [122]. There are numerous FOSH methods that have been developed for power monitoring [123][124][125][126], and smart meters [127][128][129] including those for institutional buildings (i.e., schools) [130].…”

Section: Fosh For Energy Conservationmentioning

confidence: 99%

Strategic Investment in Open Hardware for National Security

Pearce

2022

Technologies

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Free and open-source hardware (FOSH) development has been shown to increase innovation and reduce economic costs. This article reviews the opportunity to use FOSH as a sanction to undercut imports and exports from a target criminal country. A formal methodology is presented for selecting strategic national investments in FOSH development to improve both national security and global safety. In this methodology, first the target country that is threatening national security or safety is identified. Next, the top imports from the target country as well as potentially other importing countries (allies) are quantified. Hardware is identified that could undercut imports/exports from the target country. Finally, methods to support the FOSH development are enumerated to support production in a commons-based peer production strategy. To demonstrate how this theoretical method works in practice, it is applied as a case study to a current criminal military aggressor nation, who is also a fossil-fuel exporter. The results show that there are numerous existing FOSH and opportunities to develop new FOSH for energy conservation and renewable energy to reduce fossil-fuel-energy demand. Widespread deployment would reduce the concomitant pollution, human health impacts, and environmental desecration as well as cut financing of military operations.

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Revealing Characteristic IoT Behaviors by Performing Simple Energy Measurements via Open Hardware/Software Components

Cited by 6 publications

References 13 publications

An On-Device Learning System for Estimating Liquid Consumption from Consumer-Grade Water Bottles and Its Evaluation

An On-Device Learning System for Estimating Liquid Consumption from Consumer-Grade Water Bottles and Its Evaluation

Design and Implementation of an Urban Farming Robot

Strategic Investment in Open Hardware for National Security

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