298
G. K. Shankhdhar et al.
The authors in this chapter present the work which is the outcome of a research
effort that focuses on discovery and seeks for the minimum concepts and relationships
that can provide answers to most of the end user queries in the farming domain.
The authors have developed an ontological model, SAGRO-Lite, a part of the bigger
Multi-Agent System, ABSMSA for use in Smart Farming typically for the challenges
faced by the developing countries [29]. To avoid the delays, complexity and not so
profitable features, ABSMSA utilizes the IoT-Lite Meta Model for performance
improvements and also provides a smart agriculture ontology tailored for use by
farmers in the developing countries like India. Semantic modeling is only the initial
part of the whole design, SAGRO-Lite with its agents has to take into account how the
models will be used; how the annotated data will be indexed and queried with realtime data; and how to make the publication suitable for constrained environments and
large scale deployments when applications often require low latency and processing
time. All events triggered by the sensors are handled by a dedicated ontology called
are Complex Event Service Ontology discussed in earlier sections [81].
The farmers in India, and other developing countries have a common problem of
lack of technological knowledge and even a greater concern arises from the farmers’
non acceptance to technological changes and up-gradation. The whole effort of the
smart agriculture will go in vain and incur huge costs if the farmers do not cooperate. While the framework provides constructive features and benefits to farmers in
developing countries, this paper presents a research plan with an overarching goal to
help ensure that the farmers in countries like India gain from the IoT [82].
The future study focuses on the potential impact of technological developments
of smart farming on the (Indian) agriculture and food sector in the long term, transcending domain boundaries and disciplines, and thus offering a view on uncertainties
and room for strategic decisions. By working with various methods of future studies
we have tried to do justice to the many uncertainties that are intrinsic to the future of
a complex domain such as agriculture and food. Despite the focus on technological
developments this study also touches the area of social problems and solutions by
reflecting on the scenarios and by looking at developments in a context of technological and non-technological trends. The future offers a wide view of the smart farming
as well as the food sector in general in developing countries like India.
References
1. Atzori, L., Iera, A., Morabito, G.: The internet of things: a survey. Comput. Netw. 54(15),
2787–2805 (2010)
2. Ray, P.P.: A survey on internet of things architectures. J. King Saud Univ.-Comput. Inf. Sci.
30(3), 291–319 (2018)
3. Elijah, O., et al.: An overview of Internet of Things (IoT) and data analytics in agriculture:
benefits and challenges. IEEE Internet Things J. 5(5), 3758–3773 (2018)
4. Khanna, A., Kaur, S.: Evolution of Internet of Things (IoT) and its significant impact in the
field of precision agriculture. Comput. Electron. Agric. 157, 218–231 (2019)
G. K. Shankhdhar et al.
The authors in this chapter present the work which is the outcome of a research
effort that focuses on discovery and seeks for the minimum concepts and relationships
that can provide answers to most of the end user queries in the farming domain.
The authors have developed an ontological model, SAGRO-Lite, a part of the bigger
Multi-Agent System, ABSMSA for use in Smart Farming typically for the challenges
faced by the developing countries [29]. To avoid the delays, complexity and not so
profitable features, ABSMSA utilizes the IoT-Lite Meta Model for performance
improvements and also provides a smart agriculture ontology tailored for use by
farmers in the developing countries like India. Semantic modeling is only the initial
part of the whole design, SAGRO-Lite with its agents has to take into account how the
models will be used; how the annotated data will be indexed and queried with realtime data; and how to make the publication suitable for constrained environments and
large scale deployments when applications often require low latency and processing
time. All events triggered by the sensors are handled by a dedicated ontology called
are Complex Event Service Ontology discussed in earlier sections [81].
The farmers in India, and other developing countries have a common problem of
lack of technological knowledge and even a greater concern arises from the farmers’
non acceptance to technological changes and up-gradation. The whole effort of the
smart agriculture will go in vain and incur huge costs if the farmers do not cooperate. While the framework provides constructive features and benefits to farmers in
developing countries, this paper presents a research plan with an overarching goal to
help ensure that the farmers in countries like India gain from the IoT [82].
The future study focuses on the potential impact of technological developments
of smart farming on the (Indian) agriculture and food sector in the long term, transcending domain boundaries and disciplines, and thus offering a view on uncertainties
and room for strategic decisions. By working with various methods of future studies
we have tried to do justice to the many uncertainties that are intrinsic to the future of
a complex domain such as agriculture and food. Despite the focus on technological
developments this study also touches the area of social problems and solutions by
reflecting on the scenarios and by looking at developments in a context of technological and non-technological trends. The future offers a wide view of the smart farming
as well as the food sector in general in developing countries like India.
References
1. Atzori, L., Iera, A., Morabito, G.: The internet of things: a survey. Comput. Netw. 54(15),
2787–2805 (2010)
2. Ray, P.P.: A survey on internet of things architectures. J. King Saud Univ.-Comput. Inf. Sci.
30(3), 291–319 (2018)
3. Elijah, O., et al.: An overview of Internet of Things (IoT) and data analytics in agriculture:
benefits and challenges. IEEE Internet Things J. 5(5), 3758–3773 (2018)
4. Khanna, A., Kaur, S.: Evolution of Internet of Things (IoT) and its significant impact in the
field of precision agriculture. Comput. Electron. Agric. 157, 218–231 (2019)