Hybrid architecture for localized agricultural information dissemination

Abstract

Use of information and communication technologies can improve the agricultural and rural development. Client server architecture in conjunction with the mobile applications on smart-phones can be useful for delivery of the precise agricultural information to the farmers. Geographical data of mobile phones can further localize the required information needs of the farmers. In this paper, an approach have been suggested for hybrid architecture based on mobile and web technology using the location. The inference of the decision to disseminate information can be made dynamic using an improved rule promotion technique.

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

“…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.…”

“…Information Localization. In order to provide relevant information to farmers, Jain et al proposed a hybrid architecture which combines mobile and web technology and uses the location of mobile device to improve the information sent to farmers [31]. The main purpose of this paper is to design a system that can provide the localized information which is very crucial at one location but may be irrelevant to other locations.…”

“…The applications discussed above provide innovative solutions, but only for a subset of the information needs. Reference [31] is a general solution which is applicable to all stages, while [20,32] provide solutions that take crowdsourcing approaches for context stage.…”

“…Some applications that were reviewed pose some challenges due to the nature of the approaches taken by the application. Saha et al [22] and Jain et al [31] took the crowdsourcing approach to assist with the management of pest and disease outbreaks. While this approach allows rapid and distributed data to be inputted to the system, which has advantages over traditional centralized approach, the nature of crowdsourcing approach requires checking of the correctness of the data.…”

Smart paddy field monitoring system using deep learning and IoT

“…The amount of food production needed by future generations will only be fulfilled by implementing new technology (De Clercq et al, 2018; Godfray et al, 2010). “A hybrid architecture is used for localized agricultural information dissemination, which is the client-server architecture, in conjunction with mobile applications on smartphones, which can be used to deliver precise agricultural information to the farmers (Chen et al, 2012; Jain et al, 2014). ” Besides the agricultural field, the application of IoT and deep learning is utilized in the diverse area (Lin, 2020; Peixoto et al, 2020; Singh et al, 2020; Yang et al, 2020).…”