Exploring the Use of Machine Learning and the Internet of Things in Intelligent Agriculture: Short Survey
Agriculture is evolving towards more sustainable practices thanks to the integration of the machine learning and Internet of Things, which addresses many of the issues related to agricultural production and leads to increased yields with reduced input and labor costs. Smart farming has developed solutions to many conventional agricultural problems to automatically manage and monitor farmland. These technologies reduce the risk of field management in the event of bad weather, and also provide benefits to farmers in the event of labor shortages. The Internet of Things ensures the connection of physical objects that are equipped with sensors to the internet, enabling them to collect and exchange data and communicate with each other and with computer systems to gather information, perform analysis and take actions in real time that require rapid data analysis, and this task can be accomplished through machine learning algorithms with greater efficiency and high-quality decision-making. In addition, we carry out an in-depth state-of-the-art survey to identify very recent work that has implemented the Internet of Things and machine learning in smart agriculture, analyzing the development of practical solutions and discussing recent research trends and future prospects.
Authors
- Rachid Ait Daoud
- Mohamed El Mohadab
- Karim Abouelmehdi (ORCID: https://orcid.org/0009-0007-8904-8762)
- Karima El Majdouby
Institutions
- Université Sultan Moulay Slimane (MA)
- Chouaib Doukkali University (MA)
Publication Details
- Published
- 2024-10-17
- DOI
- https://doi.org/10.1109/icoa62581.2024.10754078
- Primary Topic
- Diverse Topics in Contemporary Research
- Type
- article
- Field-Weighted Citation Impact
- 0.00