Internet of Things in Agriculture for Smart Farming

Fadziso, Takudzwa

doi:10.18034/mjmbr.v5i2.565

Cited by 3 publications

(3 citation statements)

References 11 publications

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“…Agribot [72] IoT Spraying plant protection chemicals in farms Surveybot [72] IoT To provide aerial survey services of crop by LiDAR drones.…”

Section: Smart Greenhousementioning

confidence: 99%

IoT based Agriculture (IoTA): Architecture, Cyber Attack, Cyber Crime and Digital Forensics Challenges

Rudrakar¹,

Rughani²

2022

Preprint

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The Internet of Things (IoT) is a thriving technology in almost all fields of human life to make their lives easy. Smart Agriculture is one of the IoT applications on which farmers are widely switching to improve productivity and reduce labor costs. As IoT involves the Internet, data transmission technology creates the possibility of privacy/security breaches concerning users’ data. The cybercrime rate may also increase in IoT-based agriculture (IoTA). Thus there must be ready concerning digital forensics in IoTA. Various review articles are available regarding the emerging cyber attack, cybercrime, and forensics challenges in IoT applications like smart home, smart city, smart healthcare, smart grid, smart retail, smart supply chain management, and smart agriculture, while a few review articles on IoTA security and forensic challenges. This review paper is focused on IoTA solutions and their security and forensics challenges. The systematic literature review method has been used for this study which includes articles published from 2011 - 2021. This article has brought the limelight on IoT architecture and its application in agricluture (IoTA) to emphasize on its introduction, architecture, challenges and issues related emerging cybercrimes and digital forensics. At the end, this review paper discusses various challenges in securing IoTA systems and presents future directions for research.

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“…Agribot [72] IoT Spraying plant protection chemicals in farms Surveybot [72] IoT To provide aerial survey services of crop by LiDAR drones.…”

Section: Smart Greenhousementioning

confidence: 99%

IoT based Agriculture (IoTA): Architecture, Cyber Attack, Cyber Crime and Digital Forensics Challenges

Rudrakar¹,

Rughani²

2022

Preprint

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“…The idea suggests that farmers must follow standards and use hardware that includes automated processes and autonomous systems that enable a smart decision-making process. Hence, it infers the utilization of drones, robots and a few other types of AI (Fadziso, 2018a). In usual cases, farms have required numerous workers, mostly during the seasons, to collect harvests and keep the farms running.…”

Section: Evolution Of Agriculture 50mentioning

confidence: 99%

“…The crop care model traverses directly from the planting of seeds as a start point till the phase of harvesting as the end goal. The complex organized information obtained from IoT sensors from the fields is examined alongside the information gathered from bits of information alongside domain expert reviews anywhere required through Artificial Intelligence strategies (Fadziso, 2018a). After the examination of complete information, the general thing to do is to infer out of PID (Proportional Integral and Differential) regulator system.…”

Section: Crop Care Servicementioning

confidence: 99%

Implementation of Artificial Intelligence in Agriculture: A Review for CMS Optimization

Fadziso

2019

Malays. j. med. biol. res.

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Agriculture has a critical role to play in the financial domain. Likewise, automation of multiple processes in agriculture has been a great concern as well as an alarming subject across the world. The population all over the world is growing at a high rate and with this increment, demand for agriculture and its jobs is also growing exponentially. The usual techniques that were used by the farmers are not efficient enough to meet these requirements. Along these lines, new digital techniques are presented. These new strategies satisfy the proper management of agricultural products as well as services so that farmers can make the most of technology to increase their profit rates. AI in the agricultural landscape has initiated a revolutionary change. It has guarded the harvest yield from different declining factors such as environmental changes, over population, dynamic business demands, and food safety issues. By using artificial intelligence we can foster smart farming practices to limit the loss of farmers and give them high returns. Using artificial intelligence platforms, one can collect an enormous amount of information from government and public sites or real-time monitoring and collection of different information is likewise possible by utilizing IoT (Internet of Things) and afterward can be explored with precision to empower the farmers for resolving every one of the issues faced by farmers in the agriculture area. This research is conducted in order to help local farmers everywhere in the world to manage their agriculture practices all the more effectively. The strategy discussed in this paper is leveraging the model of waterfall methodology for planning and creating a system smart enough by performing a sequential cycle that starts with data collection, requirement analysis, plan, coding, and testing and finally implements that system as a whole. This system can also be used to foster ideas to manage normal issues in agriculture information systems, to improve the policy programs, the augmentation, and analysis practices, and to manage data on agriculture. Finally, conclusion about agricultural information systems are discussed and suggestions for additional development of agriculture data systems is presented.

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IoT based Agriculture (Ag-IoT): A detailed study on Architecture, Security and Forensics

Rudrakar,

Rughani

2024

Information Processing in Agriculture

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Internet of Things in Agriculture for Smart Farming

Cited by 3 publications

References 11 publications

IoT based Agriculture (IoTA): Architecture, Cyber Attack, Cyber Crime and Digital Forensics Challenges

IoT based Agriculture (IoTA): Architecture, Cyber Attack, Cyber Crime and Digital Forensics Challenges

Implementation of Artificial Intelligence in Agriculture: A Review for CMS Optimization

IoT based Agriculture (Ag-IoT): A detailed study on Architecture, Security and Forensics

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