COMPARATIVE ANALYSIS OF POWER CONSUMPTION AND REAL-TIME PERFORMANCE BETWEEN ESP32 AND RASPBERRY PI PICO W IN IOT-BASED TEMPERATURE MONITORING SYSTEMS

Power efficiency and real-time performance are two essential aspects in the development of Internet of Things (IoT) systems, especially for temperature monitoring applications operated continuously with limited energy resources. This study aims to compare two widely used microcontroller platforms—ESP32 and Raspberry Pi Pico W—in the context of an IoT-based temperature monitoring system using the DHT22 sensor and Wi-Fi communication. A quantitative experimental approach was employed, including measurement of average power consumption, system response time, and initial booting time over more than 100 operation cycles. The results show that Raspberry Pi Pico W consumes significantly less power (90 mA) than ESP32 (160 mA). However, ESP32 outperformed in real-time response, recording an average latency of 240 ms, while Pico W recorded 310 ms. Pico W also demonstrated faster boot time (950 ms) compared to ESP32 (1500 ms), which is beneficial in deep sleep scenarios. These findings highlight a trade-off between power efficiency and system responsiveness. This study contributes practically by providing a technical basis for selecting suitable microcontroller platforms based on application-specific needs. The results may serve as a reference for developing energy-efficient and responsive embedded systems, particularly in agriculture, healthcare, and smart home sectors.

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Publication Details

Journal
JURNAL TEKNOLOGI INFORMASI DAN KOMUNIKASI
Published
2025-03-01
DOI
https://doi.org/10.51903/jtikp.v16i1.1147
Citations
1
Primary Topic
IoT-based Smart Home Systems
Type
article
Field-Weighted Citation Impact
0.73
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article

COMPARATIVE ANALYSIS OF POWER CONSUMPTION AND REAL-TIME PERFORMANCE BETWEEN ESP32 AND RASPBERRY PI PICO W IN IOT-BASED TEMPERATURE MONITORING SYSTEMS

Supriyanto Supriyanto, Sigit Umar Anggono
1 citations
JURNAL TEKNOLOGI INFORMASI DAN KOMUNIKASI
IoT-based Smart Home Systems
0.73
article

COMPARATIVE ANALYSIS OF POWER CONSUMPTION AND REAL-TIME PERFORMANCE BETWEEN ESP32 AND RASPBERRY PI PICO W IN IOT-BASED TEMPERATURE MONITORING SYSTEMS

Supriyanto Supriyanto, Sigit Umar Anggono
article en
1 citations

Abstract

Power efficiency and real-time performance are two essential aspects in the development of Internet of Things (IoT) systems, especially for temperature monitoring applications operated continuously with limited energy resources. This study aims to compare two widely used microcontroller platforms—ESP32 and Raspberry Pi Pico W—in the context of an IoT-based temperature monitoring system using the DHT22 sensor and Wi-Fi communication. A quantitative experimental approach was employed, including measurement of average power consumption, system response time, and initial booting time over more than 100 operation cycles. The results show that Raspberry Pi Pico W consumes significantly less power (90 mA) than ESP32 (160 mA). However, ESP32 outperformed in real-time response, recording an average latency of 240 ms, while Pico W recorded 310 ms. Pico W also demonstrated faster boot time (950 ms) compared to ESP32 (1500 ms), which is beneficial in deep sleep scenarios. These findings highlight a trade-off between power efficiency and system responsiveness. This study contributes practically by providing a technical basis for selecting suitable microcontroller platforms based on application-specific needs. The results may serve as a reference for developing energy-efficient and responsive embedded systems, particularly in agriculture, healthcare, and smart home sectors.

JURNAL TEKNOLOGI INFORMASI DAN KOMUNIKASIVol. 16(1)
Universitas Sains dan Teknologi Jayapura (ID), Universitas Komputer Indonesia (ID), Universitas Teknologi Indonesia (ID), Universitas Sains dan Teknologi Komputer
Openalex Percentile: Top 27%
IoT-based Smart Home Systems
0.73
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COMPARATIVE ANALYSIS OF POWER CONSUMPTION AND REAL-TIME PERFORMANCE BETWEEN ESP32 AND RASPBERRY PI PICO W IN IOT-BASED TEMPERATURE MONITORING SYSTEMS — Supriyanto Supriyanto, Sigit Umar Anggono · JURNAL TEKNOLOGI INFORMASI DAN KOMUNIKASI (2025) | TGRS Research Map | TGRS