Agricultural Monitoring And Management Based On Internet Of Things, Data Analytics And Artificial Intelligent Technologies: Review
||International Journal of Computer Trends and Technology (IJCTT)||
|© 2019 by IJCTT Journal|
|Year of Publication : 2019|
|Authors : Stanley Leonard Tito|
|DOI : 10.14445/22312803/IJCTT-V67I12P107|
MLA Style:Stanley Leonard Tito "Agricultural Monitoring And Management Based On Internet Of Things, Data Analytics And Artificial Intelligent Technologies: Review" International Journal of Computer Trends and Technology 67.12 (2019):28-42.
APA Style Stanley Leonard Tito. Agricultural Monitoring And Management Based On Internet Of Things, Data Analytics And Artificial Intelligent Technologies: Review International Journal of Computer Trends and Technology, 67(12),28-42.
The increase in productivity of agricultural processes is essential to improve yields and costeffectiveness using new technology like Internet of Things(IoT) and Artificial Intelligent (AI). The improvement of agricultural sensor, machine learning, wireless communication, Big data and Cloud computing technologies, stimulates the IoT in agriculture. IoT is playing a vital role in innumerable areas of protected agriculture. This study aim to analyze the recently developed IoT technologies applicable in agricultural industries. Data for this study were mined from 40 recently peer-reviewed scientific publications (2015-2019) targeting on the frequently of use of the mentioned technologies in agricultural industry. Results from the reported studies reveals that Bluetooth and LoRaWAN technologies were the most useful technologies among the reviewed technologies with (15%) followed by Mobile cellular and ZigBee technologies at about (13%) of application. However, NB-IoT technology comes the most applicable technology after ZigBee technology with about (12%). From the data collection, SigFox seems to be the next most applicable technology among the reviewed studies in agricultural industry after NB-IoT with about (11%). Wi-Fi were found the most useful technology after SigFox with an application rate of about (8%). The least applicable rate of technologies from the reviewed studies were found to be 6LowPAN and NFC with similar application rate of about (7%). The study also reveals that Machine Learning technologies were the most useful computational technologies in farm monitoring among the reviewed technologies with the application rate of (32%) followed by Edge Computing with the application rate of 24%. Cloud computing technology was happened with an application rate of 23% followed by Big data computing technology with the application rate of 21%. However, results also reveals that Big data analytics were the most useful computational technologies in animal health monitoring among the reviewed technologies with the application rate of (29%) followed by Cloud computing with the application rate of 27% and Edge computing with an application rate of 26%. Machine Learning technology were found with the application rate of 18% as expressed in section VI of the study.
 Milija Baj?eta, Petar Sekuli?, Božo Krstaji?, Slobodan Djukanovi?, and Tomo Popovi?, Senior “A Private IoT Cloud Platform for Precision Agriculture and Ecological Monitoring”, 2016.
 Meenakshi .M, and Snehal. S. Kharde “ Advance Cattle Health Monitoring System Using Arduino and IOT” ,2016.
 Kaloxylos, A., Eigenmann, R., Teye, F., Politopoulou, Z., Wolfert, S., Shrank, C. and Nicole, H. " Farm management systems and the Future Internet era. Computers and electronics in agriculture”2015.
4] Yun Shi, Zhen Wang, Xianfeng Wang, Shanwen Zhang “Internet of Things Application to Monitoring Plant Disease and Insect Pests” ,2015.
 Olakunle Elijah ; Igbafe Orikumhi ; Tharek Abdul Rahman ; Suleiman Aliyu Babale ; Stella Ifeoma Orakwue “Enabling smart agriculture in Nigeria: Application of IoT and data analytics”, 2017.
 A. A. Raneesha Madushanki1, Malka N Halgamuge, W. A. H. Surangi Wirasagoda and Ali Syed “Adoption of the Internet of Things (IoT) in Agriculture and Smart Farming towards Urban Greening: A Review” , 2019.
 Ji-chun Zhao, Jun-feng Zhang; Yu Feng ;and Jian-xin Guo “The Study and Application of the lOT Technology in Agriculture” ,2015.
 T.Vineela,, J. NagaHarini, Ch.Kiranmai, G.Harshitha, and B.AdiLakshmi “ IoT Based Agriculture Monitoring and Smart Irrigation System Using Raspberry Pi “, 2018.
 Rahul Dagar, Subhranil Som and Sunil Kumar Khatri, “Smart Farming – IoT in Agriculture” , 2018.
 Xiaojie Shi , Xingshuang, Qingxue Zhao, Huimin Liu, Lianming Xia, Xia Sun and Yemin Guo;” State-of-the-Art Internet of Things in ProtectedAgriculture “, 2019.
 Karandeep Kaur, “The Agriculture Internet of Things: A review of the concepts and implications of implementation” , 2016.
 F Bing, “The Research of lOT of Agriculture based on Three Layers Architecture”, 2016.
 Xiaojie Shi, Xingshuang An, Qingxue Zhao, Huimin Liu, Lianming Xia, Xia Sun, and Yemin Guo “Review State-ofthe- Art Internet of Things in ProtectedAgriculture”, 2019.
 George Suciu, Cristiana-Ioana Istrate and Maria-Cristina Di?u “Secure smart agriculture monitoring technique through isolation”, 2018
 Pallavi S., Jayashree D. Mallapur and Kirankumar Y. Bendigeri “Remote Sensing and Controlling of Greenhouse Agriculture Parameters based on IoT”, 2017.
 Monishanker Halder, Ananya Sarkar and Habibullah Bahar “Plant disease detection by image processing: Review”, 2019.
 A. A. Raneesha Madushanki, Malka N Halgamuge, W. A. H. Surangi Wirasagoda and Ali Syed ”Adoption of the Internet of Things (IoT) in Agriculture and Smart Farming towards Urban Greening: A Review” ,2019.
 Christian Dimkpa, Prem Bindraban, Joan E. McLean, Lydiah Gatere, Upendra Singh, and Deborah Hellums ” Methods for Rapid Testing of Plant and Soil Nutrients” , 2017.
 Rolf A. Kjellby, Linga R. Cenkeramaddi, Anders Frøytlog , Baltasar B. Lozano, Soumya J and Meghana Bhange “Longrange and Self-powered IoT Devices for Agriculture & Aquaponics Based on Multi-hop Topology” , 2019.
 Keerthana, Nivetha P, Boomika M, Mathivatahni M and Niranjanaa ”Literature Review on IOT Based Smart Security and Monitoring Devices for Agriculture” , 2018.
 Tejaswinee A. Shinde and Jayashree R. Prasad “IoT based Animal Health Monitoring with Naïve Bayes Classification”,2017.
 P.Keertana and B Vanathi “IoT Based Animal Health Monitoring and Tracking System using ZigBee “ ,2017
 T.Satish T. Bhavani and Shameena Begum “Agriculture Productivity Enhancement System using IOT”, 2017
 Milija Baj?eta, Petar Sekuli?, Božo Krstaji?, Slobodan Djukanovi?, and Tomo Popovi?, “A Private IoT Cloud Platform for Precision Agriculture and Ecological Monitoring”, 2016.
 Abdul Salam and Syed Shah “Internet of Things in Smart Agriculture: Enabling Technologies”, 2019.
 Manishkumar Dholu and K. A. Ghodinde ” Internet of Things (IoT) for Precision Agriculture Application ” , 2018.
 Mohan C. Nikam, Suraj Wagh, Priyanka Mahajan, Devayani Waghmare, and Ketan Padewar ”Animal Welfare Monitoring Using IOT : A Review”, 2018.
 Santosh Reddy, Abhijeet Pawar, Sumit Rasane and Suraj Kadam “A Survey on Crop Disease Detection and Prevention using Android Application” , 2015.
 Olakunle Elijah , Tharek Abdul Rahman, Igbafe Orikumhi, Chee Yen Leow , and M. Nour Hindia, “An Overview of Internet of Things (IoT) and Data Analytics in Agriculture: Benefits and Challenges”, 2018.
 T.Satish1 T. Bhavani and Shameena Begum “Agriculture Productivity Enhancement System using IOT”, 2017.
 Meenakshi .M and Snehal. S. Kharde “Advance Cattle Health Monitoring System Using Arduino and IOT”, 2016.
 K. A. Patil and N. R. Kale “A Model for Smart Agriculture Using IoT”, 2016.
 Ravi K and Archana S “An IoT based soil moisture monitoring on Losant platform”, 2016.
 Foughali K Fathalah K and ali Frihida “Monitoring system using Web of thingsin precision agriculture”, 2017.
 Mahammad S and Viswanathan P “A survey: Smart agriculture IoT with cloud Computing”, 2017.
 Rahul D, Subhranil S and Sunil K “Smart Farming – IoT in Agriculture”, 2018.
 Mahammad Shareef Mekala , P. Viswanathan, “A Novel Technology for Smart Agriculture Based on IoT with Cloud Computing” ,International conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC 2017).
 Dolui. K and Datta, S. K. "Comparison of edge computing implementations: Fog computing, cloudlet and mobile edge computing," Global Internet of Things Summit (GIoTS), 2017.
Internet of Things (IoT), Smart farming, Sensor data, Agriculture, Data analytics (DA).