iFarm: Development of cloud-based system of cultivation management for precision agriculture

Yukikazu, Murakami; Utomo, Slamet Kristanto Tirto; Hosono, Keita; Umezawa, Takeshi; Osawa, Noritaka

doi:10.1109/gcce.2013.6664809

Cited by 12 publications

(8 citation statements)

References 2 publications

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“…In a composition, multiple modules from the RA are combined into one module in the AA. An example of a composition could be that the data transfer and data storage module are combined into a data management module (Murakami et al 2013). In a decomposition, the module from the RA is split into numerous smaller modules in the AA.…”

Section: Methods For Deriving An Application Architecturementioning

confidence: 99%

Reference architecture design for farm management information systems: a multi-case study approach

Tummers

Tekinerdoğan

2020

Precision Agric

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One of the key elements of precision agriculture is the farm management information system (FMIS) that is responsible for data management, analytics and subsequent decision support. Various FMISs have been developed to support the management of farm businesses. A key artefact in the development of FMISs is the software architecture that defines the gross level structure of the system. The software architecture is important for understanding the system, analysing the design decisions and guiding the further development of the system based on the architecture. To assist in the design of the FMIS architecture, several reference architectures have been provided in the literature. Unfortunately, in practice, it is less trivial to derive the application architecture from these reference architectures. Two underlying reasons for this were identified. First of all, it appears that the proposed reference architectures do not specifically focus on FMIS but have a rather broad scope of the agricultural domain in general. Secondly, the proposed reference architectures do not seem to have followed the proper architecture documentation guidelines as defined in the software architecture community, lack precision, and thus impeding the design of the required application architectures. Presented in this article is a novel reference architecture that is dedicated to the specific FMIS domain, and which is documented using the software architecture documentation guidelines. In addition, the systematic approach for deriving application architectures from the proposed reference architecture is provided. To illustrate the approach, the results of multi-case study research are shown in which the presented reference architecture is used for deriving different FMIS application architectures.

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Section: Methods For Deriving An Application Architecturementioning

confidence: 99%

Reference architecture design for farm management information systems: a multi-case study approach

Tummers

Tekinerdoğan

2020

Precision Agric

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“…In many cases, it is still not clear from a full text review if any built-in sensors are used in the applications. However, we decided to include certain articles in which although the authors did not clearly specify the sensors used, we can infer from the functionalities of the applications such as retrieving location data via GPS as in [27,28,31]. We also excluded articles written in languages other than English and those of which we could not access full text.…”

Section: Inclusion and Exclusion Criteriamentioning

confidence: 99%

“…The ability to keep records of farm workers' activities such as weeding, fertilizing, and harvesting in each area of the farm at specific time, schedule farm workers to different jobs, and communicate work plans to farmers is essential for effective farm management. Murakami et al and Murakami proposed iFarm, a system designed to assist in recording field data and communicating work plans, using smartphones, a cloud server, and web browsers [27,28]. Farmers in the field use an application on smartphones to record field data and send it to a cloud server.…”

Section: Farm Managementmentioning

confidence: 99%

“…As a large number of smartphone applications in Table 2 utilize cameras and GPS, we examine further into both hardware sensors. GPS are mostly used for location-aware applications, which send/receive essential environmental information for agriculture (such as pests and diseases [20,25,32], weather, soil [15], water [15], and radiation [26]), farm management information [27][28][29], locations of accident [30], locations of fields [23], and locations of farmers [29], based on users' locations. The aforementioned locationbased information seems to be able to tolerate some levels of location inaccuracy as environmental information or locations of farmers/fields/accidents can be reported in the vicinity of meters.…”

Section: Summary Of Current Usage Of Smartphone Sensorsmentioning

confidence: 99%

“…Then, we examine challenges of building smartphone applications to meet agricultural requirements. [27,28] 2013,2014 iFarm The application sends location-aware task lists to farmers on the field n/a Location of the user is sent to the central server, which sends only the relevant information about that location back to the user GPS Information systems [20] 2014 VillageTree Application user can report pest outbreak with the device location. The information is processed and a prediction is sent to users whose location might be invaded by the pest GPS Information systems [32] 2010 SMILEX Field worker's fire blight report from the field is coupled with the location data, so the incident report can be shown on the map for better fire blight management GPS , a directional view angle that has been shown in the agricultural research to allow the estimation of LAI to be free from leaf angle distribution and leaf degree clumping Accelerometer Farm management [29] 2013 n/a Accelerometer is used to detect various body movements in order to identify farm workers' activities Accelerometer Farm management [30] 2013 SafeDriving Accelerometer is used to obtain a roll angle and pitch angle of the tractor in order to detect a rollover event Gyroscope Farm management [30] 2013 SafeDriving Gyroscope is used to obtain a roll angle and pitch angle of the tractor in order to detect a rollover event…”

Section: Challenges Of Using Smartphone-based Sensors In Agricul-mentioning

confidence: 99%

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Applications of Smartphone-Based Sensors in Agriculture: A Systematic Review of Research

2015

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Smartphones have become a useful tool in agriculture because their mobility matches the nature of farming, the cost of the device is highly accessible, and their computing power allows a variety of practical applications to be created. Moreover, smartphones are nowadays equipped with various types of physical sensors which make them a promising tool to assist diverse farming tasks. This paper systematically reviews smartphone applications mentioned in research literature that utilize smartphone built-in sensors to provide agricultural solutions. The initial 1,500 articles identified through database search were screened based on exclusion criteria and then reviewed thoroughly in full text, resulting in 22 articles included in this review. The applications are categorized according to their agricultural functions. Those articles reviewed describe 12 farming applications, 6 farm management applications, 3 information system applications, and 4 extension service applications. GPS and cameras are the most popular sensors used in the reviewed papers. This shows an opportunity for future applications to utilize other sensors such as accelerometer to provide advanced agricultural solutions.

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A Cloud Computing Based WSNs for Agriculture Management

Waghmode¹,

Harale²

2017

Techno-Societal 2016

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iFarm: Development of cloud-based system of cultivation management for precision agriculture

Cited by 12 publications

References 2 publications

Reference architecture design for farm management information systems: a multi-case study approach

Reference architecture design for farm management information systems: a multi-case study approach

Applications of Smartphone-Based Sensors in Agriculture: A Systematic Review of Research

A Cloud Computing Based WSNs for Agriculture Management

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