Deploying a Task-based Runtime System on Raspberry Pi Clusters

Gupta, Nikunj; Brandt, Steve; Wagle, Bibek; Wu, Nanmiao; Kheirkhahan, Alireza; Diehl, Patrick; Baumann, Felix W.; Kaiser, Hartmut

doi:10.1109/espm251964.2020.00007

Cited by 11 publications

(4 citation statements)

References 22 publications

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“…The service layer of the system designed from the server consists of a Raspberry Pi 4 model B minicomputer with a 1.5 GHz quad-core 64-bit processor that provides about 3 times better performance compared to the previous version, more ports and faster Internet connection, where the certified Raspbian operating system is downloaded [14]. On the Linux system, and downloading the ThingsBoard platform on this system for the purpose of reviewing all the variables and operations that the customer performs, and they occur at the packing station immediately after logging into the server by entering a fixed IP address in any web browser such as Chrome, Firefox or others.…”

Section: Service Layermentioning

confidence: 99%

Design and Implementation Smart Petrol Station Using Internet of Things

M. Baqir,

J. Motlak

2024

Internet of Things - New Insights

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The problem that still exists nowadays with the petrol station is the method of operation because the petrol station is currently operated manually. This chapter adopted an automatic fuel filling algorithm based on a Radio Frequency Identification (RFID) card that carries information about the user regarding the type of user, the available balance and the permitted amount of fuel. This data is sent via the Wi-Fi module (ESP-32S) to the IoT platform (the panel), where it is encrypted with the hashing function and the Advanced Encryption Standard (AES) algorithm before being displayed by authorized access to the platform dashboard, which is It is also encrypted with an ID and a secret number.

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Section: Service Layermentioning

confidence: 99%

Design and Implementation Smart Petrol Station Using Internet of Things

M. Baqir,

J. Motlak

2024

Internet of Things - New Insights

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“…The average Precision metric is the weighted mean of Precision scores achieved at each precision-recall curve threshold, with the increase in recall from the previous threshold used as the weight. (8) The Average Precision in eqn. ( 8) is explained as n number of thresholds, calculating the difference between the current and the next recall values and multiplying the weight by the current precision value.…”

Section: Model Evaluationmentioning

confidence: 99%

“…It has many input/output ports that help to interact with other devices. It also has a set of General Purpose Input/Output(GPIO) pins that can be used to control electronic devices for physical computing and investigate the Internet of Things (IoT) [8].…”

Section: Deploying On Rasberry Pimentioning

confidence: 99%

An Object Detection Approach for Automated Detection of Groove Line in Tube Yoke

Kulkarni,

Naregal,

Farande

et al. 2023

ITM Web Conf.

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Deep Neural Networks are designed explicitly for visionbased applications. They have become a standard method for image classification, object detection, real-time processing capabilities, and other computer vision tasks. With the intervention of human beings, it is challenging for businesses to verify that the product is appropriately created without any glitches, as this could result in human errors due to a lack of training, which could further cause losses and several complications. Thus, there is a need for a machine learning-based solution that improves work efficiency and accuracy in identifying processed and unprocessed parts. Machine Learning models have several advantages over human intervention in tasks, including consistency, speed, scalability, costeffectiveness, and improvement over time. These advantages can help organizations improve their operations and achieve better outcomes. To do this, we propose an approach that involves building a model using an object detection method, You Only Look Once (YOLO), which is then deployed on a Raspberry Pi and integrated with the assembly line to carry out the task of validating the processed parts by achieving 98% accuracy.

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“…Similarly, numerous scholars have investigated computing clusters assembled from Raspberry Pi and analyzed the performance of these clusters for various algorithms, core count, node count, costs, and power consumption [10][11][12][13][14][15]. Moreover, researchers have used Raspberry Pi in education and demonstrated that an interactive learning environment incorporating the platform increased student engagement in atmospheric or oceanic studies.…”

Section: Introductionmentioning

confidence: 99%

Development of a Low-Cost Portable Cluster for Numerical Weather Prediction

Chen

Yeh²,

Chuang³

et al. 2022

Electronics

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Numerical weather prediction (NWP) systems are crucial tools in atmospheric science education and weather forecasting, and high-performance computing (HPC) is essential for achieving such science. The goals of NWP systems are to simulate different scales of weather systems for educational purposes or to provide future weather information for operational purposes. Supercomputers have traditionally been used for NWP systems; however, supercomputers are expensive, have high power consumption, and are difficult to maintain and operate. In this study, the Raspberry Pi platform was used to develop an easily maintained high-performance NWP system with low cost and power consumption—the Improved Raspberry Pi WRF (IRPW). With 316 cores, the IRPW had a power consumption of 466 W and a performance of 200 Gflops at full load. IRPW successfully simulated a 48-h forecast with a resolution of 1 km and a domain of 32,000 km2 in 1.6 h. Thus, IRPW could be used in atmospheric science education or for local weather forecasting applications. Moreover, due to its small volume and low power consumption, it could be mounted to a portable weather observation system.

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Deploying a Task-based Runtime System on Raspberry Pi Clusters

Cited by 11 publications

References 22 publications

Design and Implementation Smart Petrol Station Using Internet of Things

Design and Implementation Smart Petrol Station Using Internet of Things

An Object Detection Approach for Automated Detection of Groove Line in Tube Yoke

Development of a Low-Cost Portable Cluster for Numerical Weather Prediction

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