Development of Tomato Harvest Support System Using Mixed Reality Head Mounted Display

Goka, Ryota; Ueda, Kazuma; Yamaguchi, S.; Kimura, Noriyuki; Iseya, Kenji; Kobayashi, Kazuma; Tomura, Toyoaki; Mitsui, Satoshi; Satake, Toshifumi; Igo, Naoki

doi:10.1109/lifetech53646.2022.9754831

Cited by 6 publications

(5 citation statements)

References 3 publications

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“…The proper time for harvesting agricultural products is not always obvious, even for experienced farmers, because fruits and vegetables have different ripening times, even on the same plant. AR could facilitate the choice of harvesting time and keep records about it in terms of traceability, as has been implemented by [51].…”

Section: Augmented Reality-assisted Traceability Along the Agricultur...mentioning

confidence: 99%

AR-Based Food Traceability as a Means for Sustainable Development

Dimou,

Styliaras,

Salomidis

2024

Sustainability

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This paper focuses on traceability as a means to ensure sustainability during food development by using augmented reality and addressing the needs of farmers/producers, development and retail companies, and consumers. After reviewing related work, the needs are outlined for an application with a highly visual interface that lets all involved parties insert, explore, and view data about food products, starting from their origin and dietary/heritage value until their placement in a market. In this direction, the research questions examined the usability of such an application along with its validity concerning whether customers would choose healthy food products based on certain criteria, ensuring sustainability at all levels. Data are selected from predefined lists where possible and propagated without disruption from farmers to markets to avoid errors. The analysis led to the AR application, FoodTrace, whose design and prototype implementation are also presented. The evaluation was encouraging as the research goals were largely met regarding both usability and content value and will help further develop the application.

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Section: Augmented Reality-assisted Traceability Along the Agricultur...mentioning

confidence: 99%

AR-Based Food Traceability as a Means for Sustainable Development

Dimou,

Styliaras,

Salomidis

2024

Sustainability

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“…If a worker lacks experience in harvesting tomatoes, they may not be able to accurately tell whether the fruits are ready for harvest or not. Therefore, a tomato harvest support system [ 54 ] has been proposed, which uses a Microsoft HoloLens, a wireless connection and a computer to process data. When tomato fruits are captured by the HoloLens, the images of the fruits are first sent to the computer for data processing, where sugar content and acidity are calculated.…”

Section: Agri-food Applicationsmentioning

confidence: 99%

“… Acidity and sugar content returned by the system. Adapted with permission from [ 54 ]. 2022, Institute of Electrical and Electronics Engineers.…”

Section: Figurementioning

confidence: 99%

Trends of Augmented Reality for Agri-Food Applications

Xie

Chai²,

O’Sullivan³

et al. 2022

Sensors

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Recent years have witnessed an increasing interest in deploying state-of-the-art augmented reality (AR) head-mounted displays (HMDs) for agri-food applications. The benefits of AR HMDs to agri-food industry stakeholders (e.g., food suppliers, retail/food service) have received growing attention and recognition. AR HMDs enable users to make healthier dietary choices, experience novel changes in their perception of taste, enhance the cooking and food shopping experience, improve productivity at work and enhance the implementation of precision farming. Therefore, although development costs are still high, the case for integration of AR in food chains appears to be compelling. This review will present the most recent developments of AR HMDs for agri-food relevant applications. The summarized applications can be clustered into different themes: (1) dietary and food nutrition assessment; (2) food sensory science; (3) changing the eating environment; (4) retail food chain applications; (5) enhancing the cooking experience; (6) food-related training and learning; and (7) food production and precision farming. Limitations of current practices will be highlighted, along with some proposed applications.

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“…In recent times, there has been an increase in the volume of literature focusing on the integration of AR within precision farming practices. For instance, Goka et al [24] proposed a harvest support system aimed at aiding tomato harvesting, utilising Microsoft HoloLens for visualising the sugar content and acidity levels of individual tomatoes. Additionally, augmented reality techniques have been employed to facilitate the identification of weeds [25], plants [26], and pests [27], where users could be guided to the location that needs intervention.…”

Section: Introductionmentioning

confidence: 99%

Real-Time Detection of Strawberry Ripeness Using Augmented Reality and Deep Learning

Chai,

Xu,

O’Sullivan

2023

Sensors

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Currently, strawberry harvesting relies heavily on human labour and subjective assessments of ripeness, resulting in inconsistent post-harvest quality. Therefore, the aim of this work is to automate this process and provide a more accurate and efficient way of assessing ripeness. We explored a unique combination of YOLOv7 object detection and augmented reality technology to detect and visualise the ripeness of strawberries. Our results showed that the proposed YOLOv7 object detection model, which employed transfer learning, fine-tuning and multi-scale training, accurately identified the level of ripeness of each strawberry with an mAP of 0.89 and an F1 score of 0.92. The tiny models have an average detection time of 18 ms per frame at a resolution of 1280 × 720 using a high-performance computer, thereby enabling real-time detection in the field. Our findings distinctly establish the superior performance of YOLOv7 when compared to other cutting-edge methodologies. We also suggest using Microsoft HoloLens 2 to overlay predicted ripeness labels onto each strawberry in the real world, providing a visual representation of the ripeness level. Despite some challenges, this work highlights the potential of augmented reality to assist farmers in harvesting support, which could have significant implications for current agricultural practices.

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Development of Tomato Harvest Support System Using Mixed Reality Head Mounted Display

Cited by 6 publications

References 3 publications

AR-Based Food Traceability as a Means for Sustainable Development

AR-Based Food Traceability as a Means for Sustainable Development

Trends of Augmented Reality for Agri-Food Applications

Real-Time Detection of Strawberry Ripeness Using Augmented Reality and Deep Learning

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