300
G. K. Shankhdhar et al.
29. Pandey, R., Dwivedi, S.: Ontology description using owl to support semantic web applications.
Int. J. Comput. Appl. 14(4), 30–33 (2011)
30. Postel, S., et al.: Drip irrigation for small farmers: a new initiative to alleviate hunger and
poverty. Water Int. 26(1), 3–13 (2001)
31. Pandey, R., Dwivedi, S.: Interoperability between semantic web layers: a communicating agent
approach. Int. J. Comput. Appl. 12(3), 0975–8887 (2010)
32. Pandey, M., Pandey, R.: JSON and its use in semantic web. Int. J. Comput. Appl. 164(11),
10–16 (2017)
33. Kuruvilla, A., Jacob, K.S.: Poverty, social stress and mental health. Indian J. Med. Res. 126(4),
273 (2007)
34. Kumari, Sneha, et al. “Sparql: semantic information retrieval by embedding prepositions. Int.
J. Netw. Secur. Appl. 6(1), 49 (2014)
35. Pandey, R., Dwivedi, S.: RDF/RDF-S providing framework support to OWL ontologies. Int.
J. Comput. Sci. Inf. Technol. 3(4) (2012)
36. Jagannathan, S., Priyatharshini, R.: Smart farming system using sensors for agricultural
task automation. In: 2015 IEEE Technological Innovation in ICT for Agriculture and Rural
Development (TIAR), IEEE (2015)
37. Channe, H., Kothari, S., Kadam, D.: Multidisciplinary model for smart agriculture using
internet-of-things (IoT), sensors, cloud-computing, mobile-computing and big-data analysis.
Int. J. Comput. Technol. Appl. 6(3), 374–382 (2015)
38. Khatri-Chhetri, A., et al.: Farmers’ prioritization of climate-smart agriculture (CSA) technologies. Agric. Syst. 151, 184–191 (2017)
39. Patil, A., et al.: Smart farming using Arduino and data mining. In: 2016 3rd International
Conference on Computing for Sustainable Global Development (INDIACom), IEEE (2016)
40. Auernhammer, H.: Precision farming—the environmental challenge. Comput. Electron. Agric.
30(1-3), 31–43 (2001)
41. Katyal, N., Pandian, B.J.: A comparative study of conventional and smart farming. In: Emerging
Technologies for Agriculture and Environment, pp. 1–8. Springer, Singapore (2020)
42. Bronson, K.: Looking through a responsible innovation lens at uneven engagements with digital
farming. NJAS-Wageningen J. Life Sci. (2019)
43. Carolan, M.: Publicising food: big data, precision agriculture, and co-experimental techniques
of addition. Sociologia Ruralis 57(2), 135–154 (2017)
44. Popovi´ c, T., et al.: Architecting an IoT-enabled platform for precision agriculture and ecological
monitoring: a case study. Comput. Electron. Agric. 140, 255–265 (2017)
45. Atzori, L., Iera, A., Morabito, G.: Understanding the Internet of Things: definition, potentials,
and societal role of a fast evolving paradigm. Ad Hoc Netw. 56, 122–140 (2017)
46. Kamilaris, A., et al.: Agri-IoT: a semantic framework for Internet of Things-enabled smart
farming applications. In: 2016 IEEE 3rd World Forum on Internet of Things (WF-IoT), IEEE
(2016)
47. Ilapakurti, A., Vuppalapati, C.: Building an IoT framework for connected dairy. In: 2015 IEEE
First International Conference on Big Data Computing Service and Applications, IEEE (2015)
48. Madsen, S.L., et al.: Quantifying behaviour of dairy cows via multi-stage support vector
machines: book of proceedings. In: 8th European Conference on Precision Livestock Farming
(2017)
49. Sinha, R.S., Wei, Y., Hwang, S.-H.: A survey on LPWA technology: LoRa and NB-IoT. Ict
Express 3(1), 14–21 (2017)
50. Pham, C., Rahim, A., Cousin, P.: Low-cost, long-range open IoT for smarter rural African
villages. In: 2016 IEEE International Smart Cities Conference (ISC2), IEEE (2016)
51. Shaikh, F.K., Zeadally, S.: Energy harvesting in wireless sensor networks: a comprehensive
review. Renew. Sustain. Energy Rev. 55, 1041–1054 (2016)
52. Wen, Z., et al.: Self-powered textile for wearable electronics by hybridizing fiber-shaped
nanogenerators, solar cells, and supercapacitors. Sci. Adv. 2(10), e1600097 (2016)
53. Francesco, A.,et al.: Combined finite–discrete numerical modeling of runout of the Torgiovannetto di Assisi rockslide in central Italy. Int. J. Geomech. 16(6), 04016019 (2016)
G. K. Shankhdhar et al.
29. Pandey, R., Dwivedi, S.: Ontology description using owl to support semantic web applications.
Int. J. Comput. Appl. 14(4), 30–33 (2011)
30. Postel, S., et al.: Drip irrigation for small farmers: a new initiative to alleviate hunger and
poverty. Water Int. 26(1), 3–13 (2001)
31. Pandey, R., Dwivedi, S.: Interoperability between semantic web layers: a communicating agent
approach. Int. J. Comput. Appl. 12(3), 0975–8887 (2010)
32. Pandey, M., Pandey, R.: JSON and its use in semantic web. Int. J. Comput. Appl. 164(11),
10–16 (2017)
33. Kuruvilla, A., Jacob, K.S.: Poverty, social stress and mental health. Indian J. Med. Res. 126(4),
273 (2007)
34. Kumari, Sneha, et al. “Sparql: semantic information retrieval by embedding prepositions. Int.
J. Netw. Secur. Appl. 6(1), 49 (2014)
35. Pandey, R., Dwivedi, S.: RDF/RDF-S providing framework support to OWL ontologies. Int.
J. Comput. Sci. Inf. Technol. 3(4) (2012)
36. Jagannathan, S., Priyatharshini, R.: Smart farming system using sensors for agricultural
task automation. In: 2015 IEEE Technological Innovation in ICT for Agriculture and Rural
Development (TIAR), IEEE (2015)
37. Channe, H., Kothari, S., Kadam, D.: Multidisciplinary model for smart agriculture using
internet-of-things (IoT), sensors, cloud-computing, mobile-computing and big-data analysis.
Int. J. Comput. Technol. Appl. 6(3), 374–382 (2015)
38. Khatri-Chhetri, A., et al.: Farmers’ prioritization of climate-smart agriculture (CSA) technologies. Agric. Syst. 151, 184–191 (2017)
39. Patil, A., et al.: Smart farming using Arduino and data mining. In: 2016 3rd International
Conference on Computing for Sustainable Global Development (INDIACom), IEEE (2016)
40. Auernhammer, H.: Precision farming—the environmental challenge. Comput. Electron. Agric.
30(1-3), 31–43 (2001)
41. Katyal, N., Pandian, B.J.: A comparative study of conventional and smart farming. In: Emerging
Technologies for Agriculture and Environment, pp. 1–8. Springer, Singapore (2020)
42. Bronson, K.: Looking through a responsible innovation lens at uneven engagements with digital
farming. NJAS-Wageningen J. Life Sci. (2019)
43. Carolan, M.: Publicising food: big data, precision agriculture, and co-experimental techniques
of addition. Sociologia Ruralis 57(2), 135–154 (2017)
44. Popovi´ c, T., et al.: Architecting an IoT-enabled platform for precision agriculture and ecological
monitoring: a case study. Comput. Electron. Agric. 140, 255–265 (2017)
45. Atzori, L., Iera, A., Morabito, G.: Understanding the Internet of Things: definition, potentials,
and societal role of a fast evolving paradigm. Ad Hoc Netw. 56, 122–140 (2017)
46. Kamilaris, A., et al.: Agri-IoT: a semantic framework for Internet of Things-enabled smart
farming applications. In: 2016 IEEE 3rd World Forum on Internet of Things (WF-IoT), IEEE
(2016)
47. Ilapakurti, A., Vuppalapati, C.: Building an IoT framework for connected dairy. In: 2015 IEEE
First International Conference on Big Data Computing Service and Applications, IEEE (2015)
48. Madsen, S.L., et al.: Quantifying behaviour of dairy cows via multi-stage support vector
machines: book of proceedings. In: 8th European Conference on Precision Livestock Farming
(2017)
49. Sinha, R.S., Wei, Y., Hwang, S.-H.: A survey on LPWA technology: LoRa and NB-IoT. Ict
Express 3(1), 14–21 (2017)
50. Pham, C., Rahim, A., Cousin, P.: Low-cost, long-range open IoT for smarter rural African
villages. In: 2016 IEEE International Smart Cities Conference (ISC2), IEEE (2016)
51. Shaikh, F.K., Zeadally, S.: Energy harvesting in wireless sensor networks: a comprehensive
review. Renew. Sustain. Energy Rev. 55, 1041–1054 (2016)
52. Wen, Z., et al.: Self-powered textile for wearable electronics by hybridizing fiber-shaped
nanogenerators, solar cells, and supercapacitors. Sci. Adv. 2(10), e1600097 (2016)
53. Francesco, A.,et al.: Combined finite–discrete numerical modeling of runout of the Torgiovannetto di Assisi rockslide in central Italy. Int. J. Geomech. 16(6), 04016019 (2016)