Low Light Energy Autonomous LoRaWAN Node

Meli, Marcel; Brütsch, Manuel; Stajic, Stefan; Bobel, Manuel; Lorenz, David; Hegetschweiler, Lukas; Karanassos, Dimitris; Kouzinopoulos, C.

doi:10.1109/idaacs-sws50031.2020.9297089

Cited by 4 publications

(3 citation statements)

References 12 publications

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“…The system was based on a Cortex-M0 microcontroller unit (MCU) with the AEM10941 PMIC, the BME680 environmental sensor, and the RSL10 and SX1261 ICs for bluetooth low energy (BLE) and LoRa wireless communication, respectively. An autonomous LoRaWAN node for environmental monitoring of buildings was presented in [17]. The node used a LoRa SX1276 transceiver, together with an Ambiq Apollo2 MCU based on a Cortex-M4 core, a BME680 environmental sensor, and a Fujitsu ferroelectric random access memory (FRAM).…”

Section: Related Workmentioning

confidence: 99%

LP-OPTIMA: A Framework for Prescriptive Maintenance and Optimization of IoT Resources for Low-Power Embedded Systems

Papaioannou,

Dimara,

Kouzinopoulos

et al. 2024

Sensors

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Low-power embedded systems have been widely used in a variety of applications, allowing devices to efficiently collect and exchange data while minimizing energy consumption. However, the lack of extensive maintenance procedures designed specifically for low-power systems, coupled with constraints on anticipating faults and monitoring capacities, presents notable difficulties and intricacies in identifying failures and customized reaction mechanisms. The proposed approach seeks to address the gaps in current resource management frameworks and maintenance protocols for low-power embedded systems. Furthermore, this paper offers a trilateral framework that provides periodic prescriptions to stakeholders, a periodic control mechanism for automated actions and messages to prevent breakdowns, and a backup AI malfunction detection module to prevent the system from accessing any stress points. To evaluate the AI malfunction detection module approach, three novel autonomous embedded systems based on different ARM Cortex cores have been specifically designed and developed. Real-life results obtained from the testing of the proposed AI malfunction detection module in the developed embedded systems demonstrated outstanding performance, with metrics consistently exceeding 98%. This affirms the efficacy and reliability of the developed approach in enhancing the fault tolerance and maintenance capabilities of low-power embedded systems.

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Section: Related Workmentioning

confidence: 99%

LP-OPTIMA: A Framework for Prescriptive Maintenance and Optimization of IoT Resources for Low-Power Embedded Systems

Papaioannou,

Dimara,

Kouzinopoulos

et al. 2024

Sensors

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“…Measurements of various parameters were transmitted using the LoRaWAN in SF7BW125 mode with +8 dBm RF output power, allowing the coverage of a small building. After a cold start, measurement and communication were possible every 10 min at low illuminances [38]. The combination of the MCU with serial FRAM (Ferroelectric Random Access Memory) allowed critical LoRaWAN information to be kept even in the absence of power.…”

Section: Systems Working At 30 Lux or Belowmentioning

confidence: 99%

Energy Autonomous Wireless Sensing Node Working at 5 Lux from a 4 cm2 Solar Cell

Meli

Favre

Maij

et al. 2023

JLPEA

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Harvesting energy for IoT nodes in places that are permanently poorly lit is important, as many such places exist in buildings and other locations. The need for energy-autonomous devices working in such environments has so far received little attention. This work reports the design and test results of an energy-autonomous sensor node powered solely by solar cells. The system can cold-start and run in low light conditions (in this case 20 lux and below, using white LEDs as light sources). Four solar cells of 1 cm2 each are used, yielding a total active surface of 4 cm2. The system includes a capacitive sensor that acts as a touch detector, a crystal-accurate real-time clock (RTC), and a Cortex-M3-compatible microcontroller integrating a Bluetooth Low Energy radio (BLE) and the necessary stack for communication. A capacitor of 100 μF is used as energy storage. A low-power comparator monitors the level of the energy storage and powers up the system. The combination of the RTC and touch sensor enables the MCU load to be powered up periodically or using an asynchronous user touch activity. First tests have shown that the system can perform the basic work of cold-starting, sensing, and transmitting frames at +0 dBm, at illuminances as low as 5 lux. Harvesting starts earlier, meaning that the potential for full function below 5 lux is present. The system has also been tested with other light sources. The comparator is a test chip developed for energy harvesting. Other elements are off-the-shelf components. The use of commercially available devices, the reduced number of parts, and the absence of complex storage elements enable a small node to be built in the future, for use in constantly or intermittently poorly lit places.

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“…However, it is a real problem in complex industrial environments or in case of long-range transmission. Some articles present the restart after a phase without energy recovery [27], and to avoid the cold start, a preload is sometimes used during laboratory tests [28]. But very few papers address the cold start issue [29] [30].…”

Section: Battery Free Systemmentioning

confidence: 99%

Battery-Free Power Supply for Wireless Sensor Combining Photovoltaic Cells and Supercapacitors

Boitier¹,

Estibals²,

Huet³

et al. 2023

EPE

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This article exhibits the sizing, modelling, and characterization of a power supply (output 3.3 V, 200 mA max, 11 days full autonomy) dedicated to powering a wireless sensor node without a battery but usable as simply as with a battery. This system is modular for various light levels (indoor and outdoor). It is easily integrable into a sensor node, using only commercial circuits. The choices of the photovoltaic surface (amorphous silicon, η 5%, 35 cm 2 ) and of the supercapacitors value (2x 25F, 2.7 V) are explained for permanent operation, considering the solar potential and the consumption. An original part of the paper is devoted to the issue of the startup, in which we demonstrate that after a particular preload, once installed, the device can start on request at the desired time (within 15 days) using as a trigger any light source, such as the LED of a mobile phone.

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Low Light Energy Autonomous LoRaWAN Node

Cited by 4 publications

References 12 publications

LP-OPTIMA: A Framework for Prescriptive Maintenance and Optimization of IoT Resources for Low-Power Embedded Systems

LP-OPTIMA: A Framework for Prescriptive Maintenance and Optimization of IoT Resources for Low-Power Embedded Systems

Energy Autonomous Wireless Sensing Node Working at 5 Lux from a 4 cm2 Solar Cell

Battery-Free Power Supply for Wireless Sensor Combining Photovoltaic Cells and Supercapacitors

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