Optimising SD Saving Events to Maximise Battery Lifetime for Arduino™/Atmega328P Data Loggers

Bradley, Luke J.; Wright, Nick

doi:10.1109/access.2020.3041373

Cited by 14 publications

(13 citation statements)

References 16 publications

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“…The MCU, an ATmega328PB, controls the other components of the printed circuit board (PCB) and handles the interface with the output. The ATmega328PB was chosen due to its ease of use and familiarity within sensing and datalogging applications [ 41 ]. A KXTJ3-1057 accelerometer measures the local acceleration of gravity to determine the orientation of the sensor.…”

Section: Methodsmentioning

confidence: 99%

A Low-Cost Radar-Based IoT Sensor for Noncontact Measurements of Water Surface Velocity and Depth

Catsamas

Shi

Wang

et al. 2023

Sensors

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We designed an out-of-water radar water velocity and depth sensor, which is unique due to its low cost and low power consumption. The sensor is a first at a cost of less than USD 50, which is well suited to previously cost-prohibited high-resolution monitoring schemes. This use case is further supported by its out-of-water operation, which provides low-effort installations and longer maintenance-free intervals when compared with in-water sensors. The inclusion of both velocity and depth measurement capabilities allows the sensor to also be used as an all-in-one solution for flowrate measurement. We discuss the design of the sensor, which has been made freely available under open-hardware and open-source licenses. The design uses commonly available electronic components, and a 3D-printed casing makes the design easy to replicate and modify. Not before seen on a hydrology sensor, we include a 3D-printed radar lens in the casing, which boosts radar sensitivity by 21 dB. The velocity and depth-sensing performance were characterised in laboratory and in-field tests. The depth is accurate to within ±6% and ±7 mm and the uncertainty in the velocity measurements ranges from less than 30% to 36% in both laboratory and field conditions. Our sensor is demonstrated to be a feasible low-cost design which nears the uncertainty of current, yet more expensive, velocity sensors, especially when field performance is considered.

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Section: Methodsmentioning

confidence: 99%

A Low-Cost Radar-Based IoT Sensor for Noncontact Measurements of Water Surface Velocity and Depth

Catsamas

Shi

Wang

et al. 2023

Sensors

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“…This reduced the current consumption during deep sleep to 21.1 and 18.6 μA, respectively, which is a reduction factor of 40. However, this MOSFET also led to a reduction in the transmission speed for SD communication from 20 to 150 ms. Further work with higher clock speed and larger SRAM is announced [15]. This work demonstrated a good option to minimize power consumption when using SD cards but only if a low sampling or transmission rate is required.…”

Section: Related Workmentioning

confidence: 99%

“…One work that optimizes the energy consumption when writing data to an SD card was done by Bradley and Wright in which the energy consumption of the Arduino Atmega328P was determined at 5 V and 16 MHz and 3.3 V and 8 MHz [15]. In each case, the SD card communication was implemented via SPI.…”

Section: Related Workmentioning

confidence: 99%

IoT on an ESP32: Optimization Methods Regarding Battery Life and Write Speed to an SD-Card

Broell¹,

Hanshans²,

Kimmerle³

2023

Edge Computing - Technology, Management and Integration

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The ESP32 is a popular microcontroller for IoT use cases. For many IoT applications (e.g., environmental sensors or wearables), a continuous power supply is either not possible or too cumbersome, requiring battery operation. However, the ESP32 has a relatively high power consumption. This chapter focuses on battery life optimization methods for this family of microcontrollers. For scenarios where data logging is relevant, methods for increasing communication speed in relation to power consumption are examined in detail. Measurements of seven different commercially available development boards were evaluated in terms of sleep modes, reduced CPU frequencies, and serial communications with the goal of better power efficiency. Therefore, the common scenario of data logging was compared with the performance and power consumption when communicating with different SD cards and CPU frequencies via the SPI and SD bus. Our test results showed that peripheral components (such as voltage regulators) have a large impact on the power consumption of the ESP32 microcontrollers, especially in sleep mode. For data logging, higher clock rates combined with high-quality SD cards and using the SD bus in 4-bit mode resulted in the lowest battery discharge.

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“…As covered in previous work, turbidity currents are random in nature and there can be many months between events [17]. As such, it is important to ensure that the power consumption of electrical circuit is minimal to ensure the datalogger can measure data during the entire period of a turbidity current [18]. The lifetime of a battery within a circuit can be estimated as:…”

Section: Battery Lifementioning

confidence: 99%

Development of a Non-Cloggable Subsea Data Logger for Harsh Turbidity Current Monitoring

Bradley,

Ruffell,

Talling

et al. 2023

OCEANS 2023 - Limerick

Self Cite

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Large submarine flows of sediment (sand and mud), known as turbidity currents, transfer and bury significant amounts of organic carbon and pollutants to the deep sea via submarine canyons. They are also significant geohazards, regularly breaking networks of seabed telecommunications cables that carry > 99% of global data that underpin the internet. Despite this, key parameters (notably their sediment concentration) in these flows are yet to be directly measured in real-time due to their inherently harsh environment that is unsuitable for commercial conductivity sensors. To address this issue, a subsea datalogger (SSDL) is developed with a planar conductivity sensor head that can measure the sediment concentration within dense turbidity currents. Unlike conventional sensors, the planar design of the SSDL's sensor prevents clogging at high sediment concentrations, allowing for continuous measurements within turbidity currents. The conductivity sensor is developed with a temperature sensor which is measured using an external 16-Bit ADC which is controlled with a SAMD21 32-Bit ARM microcontroller. The SSDL measures the temperature and the conductivity of the seawater once every 4 seconds for over a year. In an initial device test, the SSDL can record a turbidity current within the Bute Inlet, Canada. It is found that the seawater's conductivity increases with salinity concentration and decreases with sediment concentration. The SSDL developed here can thus be used for both conventional subsea datalogging applications and high turbidity current applications.

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Optimising SD Saving Events to Maximise Battery Lifetime for Arduino™/Atmega328P Data Loggers

Cited by 14 publications

References 16 publications

A Low-Cost Radar-Based IoT Sensor for Noncontact Measurements of Water Surface Velocity and Depth

A Low-Cost Radar-Based IoT Sensor for Noncontact Measurements of Water Surface Velocity and Depth

IoT on an ESP32: Optimization Methods Regarding Battery Life and Write Speed to an SD-Card

Development of a Non-Cloggable Subsea Data Logger for Harsh Turbidity Current Monitoring

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