| _version_ | 1866901985887780864 |
|---|---|
| author | Prajwal B Rakesh Shridhar Anirudha S Tadpatri Pramodh P Ugargol Ajjaiah H B M |
| author_facet | Prajwal B Rakesh Shridhar Anirudha S Tadpatri Pramodh P Ugargol Ajjaiah H B M |
| contents | The solution developed in this paper addresses the common health hazards that are generally seen in the traditional method of spraying herbicides. To maintain the good health of the plants as they grow by eradicating unnecessary plants or weeds, it is important to spray herbicides and other chemicals effectively so that they will not hinder the growth of the plant. The solution to this is by building and modeling an Autonomous Herbicide Spraying System using Artificial intelligence and the Internet of Things (IoT). This paper emphasizes the method of filtering Global Positioning System (GPS) data using a moving average filter to improvise on the autonomous navigation system of the robot. Furthermore, the robot is capable of evaluating the count of weeds whilst spraying the herbicides when the threshold is crossed. Additionally, the robot incorporates a liquid-level sensor for measuring the amount of herbicide in real-time and transmitting the same using IoT. |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_18516147 |
| institution | Zenodo |
| language | |
| publishDate | 2021 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Autonomous Herbicide Spraying System using AI and IoT Prajwal B Rakesh Shridhar Anirudha S Tadpatri Pramodh P Ugargol Ajjaiah H B M Smart agriculture; Autonomous navigation; GPS data filtering; Image processing; IoT; YOLOv5; Moving average filter. The solution developed in this paper addresses the common health hazards that are generally seen in the traditional method of spraying herbicides. To maintain the good health of the plants as they grow by eradicating unnecessary plants or weeds, it is important to spray herbicides and other chemicals effectively so that they will not hinder the growth of the plant. The solution to this is by building and modeling an Autonomous Herbicide Spraying System using Artificial intelligence and the Internet of Things (IoT). This paper emphasizes the method of filtering Global Positioning System (GPS) data using a moving average filter to improvise on the autonomous navigation system of the robot. Furthermore, the robot is capable of evaluating the count of weeds whilst spraying the herbicides when the threshold is crossed. Additionally, the robot incorporates a liquid-level sensor for measuring the amount of herbicide in real-time and transmitting the same using IoT. |
| title | Autonomous Herbicide Spraying System using AI and IoT |
| topic | Smart agriculture; Autonomous navigation; GPS data filtering; Image processing; IoT; YOLOv5; Moving average filter. |
| url | https://doi.org/10.5281/zenodo.18516147 |