Soil Monitoring and Crop Yield Prediction Using Machine Learning
Main Article Content
Abstract
Internet of Things (IoT) is a quickly developing innovation and the field of IoT is broadening its wings in all of the zones today. With the movement in PCs like Arduino the advancement is accomplishing the ground level with its application in cultivating. In this work, we have illustrated and realized observing of soil quality by using Arduino, different Sensors and Android application. Soil quality boundaries utilized in this work are temperature, soil dampness level Ammonia and carbon content. Sensor securing is led by Arduino is utilized as information handling gadget just as worker. Android phone is utilized as the terminal gadget. To improve profitability of agribusiness through astute homestead the executives, the information breaking down should be very much investigated and handled ML calculations could be applied to additional upgrade application knowledge and usefulness. In this article we audit existing methodologies have been made to the savvy agribusiness and cultivating dependent on IoT and ML independently. Additionally, we propose novel ideas that how might ML-IoT can be mixed in such applications.
Downloads
Metrics
Article Details
Licensing
TURCOMAT publishes articles under the Creative Commons Attribution 4.0 International License (CC BY 4.0). This licensing allows for any use of the work, provided the original author(s) and source are credited, thereby facilitating the free exchange and use of research for the advancement of knowledge.
Detailed Licensing Terms
Attribution (BY): Users must give appropriate credit, provide a link to the license, and indicate if changes were made. Users may do so in any reasonable manner, but not in any way that suggests the licensor endorses them or their use.
No Additional Restrictions: Users may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.