Using the mobile phone as Munsell soil-colour sensor: An experiment under controlled illumination conditions

Gómez‐Robledo, Luis; López-Ruiz, Nuria; Melgosa, Manuel; Palma, A.; Capitán-Vallvey, L.F.; Sánchez‐Marañón, M.

doi:10.1016/j.compag.2013.10.002

Cited by 125 publications

(74 citation statements)

References 32 publications

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“…The intensity of the lights was set to 75% of its capacity to avoid overheating while maintaining adequate brightness for illuminating the samples. Studies with Munsell colour chart using Konica Minolta spectrophotometer CM-2600d (Konica Minolta, Inc., Tokyo, Japan) showed that controlled lighting conditions were necessary for estimating parameters based on colour (G omez- Robledo et al, 2013). Thus the holder was designed to isolate the object under observation from any external light effects which tend to be unpredictable depending upon weather conditions.…”

Section: Instrumentation and Hardwarementioning

confidence: 99%

“…Similarly, images of the thin sections of cement impregnated with epoxy to enhance the contrast between particles have also been used in the concrete industry to categorize particle size distributions (Mertens & Elsen, 2006). An earlier attempt has also been made to characterize soil particle distribution using computer vision algorithms (Ghalib & Hryciw, 1999). A CCD camera was used to capture images of soil samples placed on a platform and illuminated with light from underneath.…”

Section: Introductionmentioning

confidence: 99%

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Microscope-based computer vision to characterize soil texture and soil organic matter

Sudarsan

Biswas

et al. 2016

Biosystems Engineering

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Section: Instrumentation and Hardwarementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Microscope-based computer vision to characterize soil texture and soil organic matter

Sudarsan

Biswas

et al. 2016

Biosystems Engineering

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“…A recent study by Gomez-Robledo et al (2013) tested the use of cell phone cameras to quantitatively determine soil color. A mobile app was developed for the experiment that would take photos of a soil sample and determine the red, green, and blue (RGB) color codes for the pixels that appeared the most in a cropped area of the photo.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of an inexpensive sensor to measure soil color

Stiglitz

Mikhailova

Post

et al. 2016

Computers and Electronics in Agriculture

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“…In addition, the smartphone-based sensors were used as soil color sensors. Soil color information was read from images taken by the built-in digital cameras on smartphones and processed using image processing techniques to transform the RGB color space into colors in XYZ and HVC spaces [13].…”

Section: Smartphone-based Sensorsmentioning

confidence: 99%

Real-Time Monitoring System Using Smartphone-Based Sensors and NoSQL Database for Perishable Supply Chain

2017

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Abstract:Since customer attention is increasing due to growing customer health awareness, it is important for the perishable food supply chain to monitor food quality and safety. This study proposes a real-time monitoring system that utilizes smartphone-based sensors and a big data platform. Firstly, we develop a smartphone-based sensor to gather temperature, humidity, GPS, and image data. The IoT-generated sensor on the smartphone has characteristics such as a large amount of storage, an unstructured format, and continuous data generation. Thus, in this study, we propose an effective big data platform design to handle IoT-generated sensor data. Furthermore, the abnormal sensor data generated by failed sensors is called outliers and may arise in real cases. The proposed system utilizes outlier detection based on statistical and clustering approaches to filter out the outlier data. The proposed system was evaluated for system and gateway performance and tested on the kimchi supply chain in Korea. The results showed that the proposed system is capable of processing a massive input/output of sensor data efficiently when the number of sensors and clients increases. The current commercial smartphones are sufficiently capable of combining their normal operations with simultaneous performance as gateways for transmitting sensor data to the server. In addition, the outlier detection based on the 3-sigma and DBSCAN were used to successfully detect/classify outlier data as separate from normal sensor data. This study is expected to help those who are responsible for developing the real-time monitoring system and implementing critical strategies related to the perishable supply chain.

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Using the mobile phone as Munsell soil-colour sensor: An experiment under controlled illumination conditions

Cited by 125 publications

References 32 publications

Microscope-based computer vision to characterize soil texture and soil organic matter

Microscope-based computer vision to characterize soil texture and soil organic matter

Evaluation of an inexpensive sensor to measure soil color

Real-Time Monitoring System Using Smartphone-Based Sensors and NoSQL Database for Perishable Supply Chain

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