Developing a smartphone app for m-government in agriculture

Karetsos, Sotiris; Costopoulou, Constantina; Sideridis, Alexander B.

doi:10.17700/jai.2014.5.1.129

Cited by 34 publications

(31 citation statements)

References 7 publications

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“…In addition, there are no studies on livestock price prediction using mobile applications. This is supported by [9] whose study shows that there are many smartphone agriculture apps on crop prices, weather conditions, inventory levels and innovative farming techniques and machinery. Despite of this fact, applications specifically geared for the agriculture sector are still limited, and livestock falls under this sector.…”

Section: Related Workmentioning

confidence: 92%

On the Development of Machine Learning – Based Application Framework for Enhancing Performance of Livestock Mobile Application Systems in Poor Internet Service Areas

Wanga¹,

Ghani²,

Kalegele³

2017

IJCA

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In this paper, authors developed an intelligent subsystem which manages training set, finds high accuracy models, selects best model to be used, computes prediction, stores in the database, and sends to the user interface through internet during online mode, and in offline mode through developed log file and filtering method. The intelligent subsystem is one of solutions which support mobile phone systems to be executed offline, on mobile device. Prediction results can be locally stored in the database and log file while in presence of a fairly good connection environment. Thereafter, offline predictions are made available when a poor quality in connection comes. System development covers intelligent subsystem, MySQL database development, log file, filtering of information, and Android application. Apart from viewing predictions basing on ElasticNet algorithm, the system allows a user to register, login, and access livestock market, information portal, information request, information responses, and submit daily records.The filtering techniques are used to select part of information from the log file. The log file created on the last online activity is used to serve all the offline operations as follows: -1) Once the user has selected the offline option in the app's interface, he/she is directed to select the breed, sex and grade. 2) Upon submission of his/her input i.e. breed, sex and grade, the system reads the log and through the filtering algorithm, the predicted price is captured and displayed to the user.Overall, this paper makes the following six key contributions; (1) Creating a mechanism to select a subset of information between livestock keeper and server. The subset of information is used when internet fails. (2) To design and implement machine learning based sub-system that is able to select frequently asked requests and make them available to livestock keepers during the offline mode. (3) To develop a subsystem, this is ad hoc and performs model selection. (4) Model creation that evaluates more than one algorithm in our setting or context. Others compared algorithms in their settings. (5) Introduction of a smaller database that replicates information, which smallholder farmers requests online and stores them to be available during offline state. (6) Using database of the phone to store vital information.

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Section: Related Workmentioning

confidence: 92%

On the Development of Machine Learning – Based Application Framework for Enhancing Performance of Livestock Mobile Application Systems in Poor Internet Service Areas

Wanga¹,

Ghani²,

Kalegele³

2017

IJCA

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“…c)Weather app-These applications are useful for the farmers for obtaining forecasts of the weather. Weather related apps are the most used applications in agriculture (Karetsos, Costopoulou, & Sideridis, 2014) e.g. skymet weather app.…”

Section: Agri-crop Mobile Applicationmentioning

confidence: 99%

Smart phone applications: Role in agri- information dissemination

Barh¹,

Balakrishnan²

2018

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Agriculture is a standout amongst the most critical imperative segments of our country. Farming contributes almost around 17.01% of India's GDP. There are different elements that affected the agriculture development; however the most essential bottlenecks are lack of instant information and drudgery involved in farming practices. To conquer these issues, agriculture should be made more alluring and done smartly. Already there are limited talks on climate smart agriculture, which aims for sustainable increase in agricultural productivity and incomes to meet out the current and future demands. Here, we are examining about how the mobile application can help agriculture development faster and hustle free. There are varieties of mobile applications, utilized over the globe for different segments, including farming, but here the usage is still is limited. We have elaborated various agricultural mobile applications which potentially can be used in farming and allied activities as indicated by their source and usage. In India, there are enormous opportunities for utilizing the smart phones as a part of agribusiness improvement. Its utilization is vital for quick growth and easy access to information to Indian agriculturists, farmers and growers.

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“…There is an app for everything -and this is also the case in agriculture. Karetsos, Costopoulou & Sideridis (2014) The mobile revolution can be observed in the whole world. According to a recent report from the International Telecommunication Union (ITU), by the end of 2015, there are more than 7 billion mobile cellular subscriptions worldwide (up from 738 million in 2000).…”

Section: Mobile Devices In Agriculture: the Same Pattern Of Adoption?mentioning

confidence: 99%

Mobile devices in agriculture: attracting new audiences or serving the tech-savvy?

Csótó¹

2015

JAI

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A B S T R A C TThe latest wave of ICT-innovations are based around mobility (smart phones, tablets, wireless networks etc.). Mobility can be a decisive success factor of ICT-adoption, because of the spatial, local and remote nature of farming. New generation mobile devices can also have a lower barrier to entry in terms of skills and cost for the user/farmer. The question is whether these new devices, especially smart phones and tablets are adopted by the farmers who are already using computers and Internet or they are attracting new audiences as well? The author's research in Hungary on the supply and demand side of the phenomenon shows that the "agri-app-economy" is still in its infancy, and both the supply and demand side are reflecting the current state and the earlier development of ICT-usage in agriculture. At the moment, new generation of mobile devices are not acting as a tool to overcome earlier and existing barriers of adoption, rather as an indicator of the general level of ICT-use in agriculture. Mobile devices are mainly used by "tech-savvy" farmers, as a general purpose technology -partly because of the lack of relevant applications in agriculture.

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Developing a smartphone app for m-government in agriculture

Cited by 34 publications

References 7 publications

On the Development of Machine Learning – Based Application Framework for Enhancing Performance of Livestock Mobile Application Systems in Poor Internet Service Areas

On the Development of Machine Learning – Based Application Framework for Enhancing Performance of Livestock Mobile Application Systems in Poor Internet Service Areas

Smart phone applications: Role in agri- information dissemination

Mobile devices in agriculture: attracting new audiences or serving the tech-savvy?

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