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Record W2995322313 · doi:10.3934/electreng.2020.1.57

Design and implementation of a low-cost, open source IoT-based SCADA system using ESP32 with OLED, ThingsBoard and MQTT protocol

2019· article· en· W2995322313 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAIMS Electronics and Electrical Engineering · 2019
Typearticle
Languageen
FieldComputer Science
TopicIoT and Edge/Fog Computing
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsSCADAMQTTComputer scienceMessage queueInteroperabilityEmbedded systemComputer networkOperating systemEngineeringInternet of ThingsElectrical engineering

Abstract

fetched live from OpenAlex

Distributed assets, such as hybrid power system components, require reliable, timely, and secure coordinated data monitoring and control systems. Supervisory Control and Data Acquisition (SCADA) is a technology for the coordinated monitoring and control of such assets. However, SCADA system designs and implementations have largely been proprietary, mostly pricey and therefore economically unjustifiable for smaller applications. With proprietary SCADA systems, there is also the problem of interoperability with the existing components such as power electronic converters, energy storage systems, and communication systems since these components are usually from multiple vendors. Therefore, an open source SCADA system represents the most flexible and most cost-effective SCADA option for such assets. In this paper, we present the design and implementation of a low-cost, open source SCADA system based on the most recent SCADA architecture, the Internet of Things (IoT). The proposed SCADA system consists of current and voltage sensors for data collection, an ESP32 micro-controller with organic light-emitting diode (OLED) display, for receiving and processing the sensor data, and ThingsBoard IoT server for historic data storage and human machine interactions. For the sensor data transfer from the ESP32 to the ThingsBoard IoT server, Message Queuing Telemetry Transport (MQTT) protocol is implemented for data transfer over a local Wi-Fi connection with the MQTT Client configured on the ESP32, and the ThingsBoard server node serving as the MQTT Broker. The ThingsBoard IoT server is locally installed with PostgreSQL database on a Raspberry Pi single-board computer and hosted locally on MUN Network for data integrity and security. To test the performance of the developed open source SCADA system solution, it was setup to acquire and process the current, voltage and power of a standalone solar photovoltaic system for remote monitoring and supervisory control. The overall system design procedures and testing, as well as the created dashboards and alarms on the ThingsBoard IoT server platform are presented in the paper.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.697
Threshold uncertainty score0.691

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.007
GPT teacher head0.240
Teacher spread0.232 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it