Semi‐portable solar power to facilitate continuous operation of technology in the field

Proppe, Darren S.; Pandit, Meelyn; Bridge, Eli S.; Jasperse, Philip; Holwerda, Charles

doi:10.1111/2041-210x.13456

Cited by 8 publications

(4 citation statements)

References 19 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…It is also possible to run the Raspberry Pi on solar energy. A small 5 V 6 W solar panel can suffice for the most basic requirements, and larger, more permanent systems can be an ideal solution for many field systems, such as including a 12 V/18 V 50 W solar panel, a solar charger and a 12 V battery (see Proppe et al., 2020; Sethi et al., 2018).…”

Section: Guidelines Pointers and Considerations For Implementing The ...mentioning

confidence: 99%

“…For example, when there is 5 hr of expected sun per day, the system should be able to run 3 days without any sun, and energy efficiency is 70%, then the solar panel should be at least 6 W ((0.35 A × 3 hr × 5 V) × 4 day/0.7/5). Real‐life power consumption tests with your system are recommended before putting it to use (see Proppe et al., 2020 for further information).…”

Section: Guidelines Pointers and Considerations For Implementing The ...mentioning

confidence: 99%

See 1 more Smart Citation

Broad‐scale applications of the Raspberry Pi: A review and guide for biologists

Jolles

2021

Methods Ecol Evol

153

View full text Add to dashboard Cite

1. The field of biology has seen tremendous technological progress in recent years, fuelled by the exponential growth in processing power and high-level computing, and the rise of global information sharing. Low-cost single-board computers are predicted to be one of the key technological advancements to further revolutionise this field.2. So far, an overview of current uptake of these devices and a general guide to help researchers integrate them in their work has been missing. In this paper I focus on the most widely used single-board computer, the Raspberry Pi, and review its broad applications and uses across the biological domain.3. Since its release in 2012, the Raspberry Pi has been increasingly taken up by biologists, in the laboratory, the field and in the classroom, and across a wide range of disciplines. A hugely diverse range of applications exists that ranges from simple solutions to dedicated custom-build devices, including nest-box monitoring, wildlife camera trapping, high-throughput behavioural recording, large-scale plant phenotyping, underwater video surveillance, closed-loop operant learning experiments and autonomous ecosystem monitoring. Despite the breadth of its implementations, the depth of uptake of the Raspberry Pi by the scientific community is still limited. 4. The broad capabilities of the Raspberry Pi, combined with its low cost, ease of use and large user community make it a great research tool for almost any project. To help accelerate the uptake of the Raspberry Pi by the scientific community, I provide detailed guidelines, recommendations and considerations, and 30+ step-by-step guides on a dedicated accompanying website (http://raspb erryp i-guide.github.io). I hope this paper will help generate more awareness about the Raspberry Pi among scientists and thereby both fuel the democratisation of science and ultimately help advance our understanding of biology, from the micro-to the macro-scale.

show abstract

Section: Guidelines Pointers and Considerations For Implementing The ...mentioning

confidence: 99%

Section: Guidelines Pointers and Considerations For Implementing The ...mentioning

confidence: 99%

Broad‐scale applications of the Raspberry Pi: A review and guide for biologists

Jolles

2021

Methods Ecol Evol

153

View full text Add to dashboard Cite

show abstract

“…In a battery-powered configuration utilizing the RPi 3B+ with an average current draw of 528 mA from a 5 V source, the operational power demand of the system is approximately 2.64 W. Employing a 50 Ah commercial power bank as the energy reserve, the effective output is calculated to be 250 Wh (50 Ah × 5 V), projecting the operational longevity of our edge device on this power supply to be around 94 h (250/2.64). Considering the variable nature of CPU usage, a conservative estimate adjusts the expected battery life to 50% of this duration [69], translating to an operational range between 47 and 94 h without the need for manual intervention. Previous work [70] has shown that integrating an RPi with a 12 V 50 W solar panel with a solar charger and a 12 V battery can facilitate continuous operation in the field, devoid of frequent maintenance needs.…”

Section: Edge Device Analysismentioning

confidence: 99%

Bat2Web: A Framework for Real-Time Classification of Bat Species Echolocation Signals Using Audio Sensor Data

Mahbub,

Bhagwagar,

Chand

et al. 2024

Sensors

View full text Add to dashboard Cite

Bats play a pivotal role in maintaining ecological balance, and studying their behaviors offers vital insights into environmental health and aids in conservation efforts. Determining the presence of various bat species in an environment is essential for many bat studies. Specialized audio sensors can be used to record bat echolocation calls that can then be used to identify bat species. However, the complexity of bat calls presents a significant challenge, necessitating expert analysis and extensive time for accurate interpretation. Recent advances in neural networks can help identify bat species automatically from their echolocation calls. Such neural networks can be integrated into a complete end-to-end system that leverages recent internet of things (IoT) technologies with long-range, low-powered communication protocols to implement automated acoustical monitoring. This paper presents the design and implementation of such a system that uses a tiny neural network for interpreting sensor data derived from bat echolocation signals. A highly compact convolutional neural network (CNN) model was developed that demonstrated excellent performance in bat species identification, achieving an F1-score of 0.9578 and an accuracy rate of 97.5%. The neural network was deployed, and its performance was evaluated on various alternative edge devices, including the NVIDIA Jetson Nano and Google Coral.

show abstract

“…Using S-MLS with solar power energy the cost will be zero in all three locations. Proppe et al (2020) stated that the solar recharge rate depends on the consistency of the sunlight. Sunlight can harvest with a maximum of 4-6 hours of direct peak.…”

Section: Research Questionmentioning

confidence: 99%

Testing the Perceived Efficacy and Value of a Solar-Powered MoodleBox to Provide Sustainable Educational Support to Underdeveloped Areas

Samaranayake

View full text Add to dashboard Cite

The dissertation aims to expand access through a low-cost technological innovation system S-MLS to learners in underdeveloped areas with difficulties in accessing education. Technology is advancing rapidly. However, many parts of the world need access to educational advances, which are hindered due to war, political situations, and low literacy and income. A qualitative phenomenological approach explores the lived experience using the solar-powered computing and learning management system (LMS) to support the development of educational access in underrepresented societies, developing countries, and rural areas where access to proper classroom education is non-existent. Proof of concept is used with a group of students in a rural area, a developing country, and within an underrepresented population to check the feasibility of using the equipment in a real-world setting. A technology acceptance model would be used to identify the user's perceived interest and user acceptance. The community of inquiry theory would find the first-hand experience and point of view of the learner. The student group interviews would be through semi-structured interviews. Observations, surveys, video/audio recordings, and artifacts would be gathered for further analysis. The data collected would be analyzed using interpretative phenomenology analysis (IPA), close examination, and management of development themes through thoughts, observations, and reflections on the technological experience and future research and implementations provided. The projected finding would be to check that a solar-powered Raspberry Pi system with MoodleBox operating system that runs Moodle (Modular Object-Oriented Dynamic Learning Environment) LMS would be feasible to provide learning underdeveloped areas to enhance education.

show abstract

Semi‐portable solar power to facilitate continuous operation of technology in the field

Cited by 8 publications

References 19 publications

Broad‐scale applications of the Raspberry Pi: A review and guide for biologists

Broad‐scale applications of the Raspberry Pi: A review and guide for biologists

Bat2Web: A Framework for Real-Time Classification of Bat Species Echolocation Signals Using Audio Sensor Data

Testing the Perceived Efficacy and Value of a Solar-Powered MoodleBox to Provide Sustainable Educational Support to Underdeveloped Areas

Contact Info

Product

Resources

About