An Automatic Sorting Machine Using Weight Sensor and Moisture Content Measurement for Sweet Potatoes

Lestari, Nina Dwi; Badri, Daffa Akbar; Khadafi, Ahmad; Munastha, Ketut Abimanyu; Sarief, Ivany; Wijaya, Wisnu

doi:10.1109/tssa56819.2022.10063888

Cited by 3 publications

(1 citation statement)

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“…HX711 has high sensitivity and can meet scene requirements to avoid safety hazards. Lestrai et al [12] used HX711 to construct a sweet potato grasping system. HX711 has high precision and can avoid damage to sweet potatoes.…”

Section: Introductionmentioning

confidence: 99%

CCICR-V1.0: An Embeded system for recording Chinese Cuisine Cooker data

Zhang,

Wang,

Bao

et al. 2024

Preprint

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The Chinese cooking process is complex and involves a wide variety of dishes, contains a large amount of data, which poses a great challenge to the intelligentization of cooking. To address this issue, this paper proposes a versatile, highly reliable, user-friendly, and intelligent data recorder for Chinese cuisine (Chinese Cuisine Intelligent Cooker Recorder-V1.0, CCICR-V1.0), which is designed to record the associated data generated during Chinese cooking and provide data support for intelligent cooking robot systems.CCICR-V1.0 is equipped with an STM32 microcontroller as the control core and integrated with temperature, pressure, and attitude sensors, enabling intelligent collection of data related to dishes, ingredients, and cookware movement during the cooking process. For high-frequency and multi-channel data acquisition tasks, CCICR-V1.0 adopts a multi-task data buffering storage method, effectively allocating CPU resources, and utilizes NAND Flash as the storage medium to ensure secure storage, management, and preservation of data. Through testing, CCICR-V1.0 has demonstrated its capability to achieve multi-channel, high-frequency data acquisition and storage in complex environments, resulting in an automation rate increase of 89.9%. The weighing module of CCICR-V1.0 exhibits a maximum relative error of 0.288%, while the non-contact infrared temperature measurement module shows a maximum absolute error and maximum relative error of only 0.65°C and 0.78%, respectively. The non-contact infrared temperature measurement module also achieves a cost reduction of 91.7% and an accuracy improvement of approximately 40%. CCICR-V1.0 effectively captures Chinese cooking data and possesses significant commercial value for widespread adoption and application.

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Section: Introductionmentioning

confidence: 99%

CCICR-V1.0: An Embeded system for recording Chinese Cuisine Cooker data

Zhang,

Wang,

Bao

et al. 2024

Preprint

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Intelligence data acquisition based on embedded system in Chinese cuisine cooker (CCICR V1.0)

Zhang,

Wang,

Bao

et al. 2024

Sci Rep

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The Chinese cooking process, intricate and diverse, encompasses a wide range of dishes, generating substantial data that often poses significant challenges for automation. To address these challenges, this paper introduces a versatile, highly reliable, user-friendly, and intelligent data recorder specifically designed for Chinese cuisine-the Chinese Cuisine Intelligent Cooker Recorder-V1.0 (CCICR-V1.0). This device is intended to record data generated during the cooking process and provide essential support for intelligent cooking robot systems. The core of CCICR-V1.0 is a STM32 microcontroller, equipped with sensors that monitor temperature, pressure, and attitude. These sensors facilitate the intelligent collection of data related to dishes, ingredients, and the movements of cookware throughout the cooking process. To ensure efficient data acquisition and storage, CCICR-V1.0 employs a multi-task data buffering storage method that effectively allocates CPU resources. NAND Flash is used as the storage medium, guaranteeing secure storage, management, and preservation of high-frequency, multi-channel data. Experimental results demonstrate the effectiveness of CCICR-V1.0 in achieving multi-channel, high-frequency data acquisition and storage in complex environments. This leads to an increase in automation efficiency of 89.9%. The weighing module demonstrates a maximum relative error of only 0.288%, while the attitude sensor experiment shows an attitude information error of just 0.22°C. Furthermore, the non-contact infrared temperature measurement module exhibits impressive performance with a maximum absolute error of 0.258 and a maximum relative error of 0.88%. Notably, this measurement module has achieved a cost reduction of approximately 91.7% and an accuracy improvement of around 40%. Additionally, the response time of CCICR-V1.0 is less than 3 ms. With its ability to effectively capture data related to Chinese cooking, CCICR-V1.0 holds commercial value for widespread adoption and application in the field of intelligent cooking.

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