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David, Fortune
- Computer Networking and Technology Improvement in the Age of COVID-19
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Authors
Affiliations
1 Hobby Researcher in Robotics, Artificial Intelligence, IOT, US
2 Cambridge Institute of Technology, Bangalore, IN
3 Facilitator, LeenaBOT Robotics, NG
1 Hobby Researcher in Robotics, Artificial Intelligence, IOT, US
2 Cambridge Institute of Technology, Bangalore, IN
3 Facilitator, LeenaBOT Robotics, NG
Source
International Journal of Advanced Networking and Applications, Vol 12, No 3 (2020), Pagination: 4592-4595Abstract
Corona virus has plagued the world and has brought the life around the world to a standstill. The virus is highly transmissible, and with no vaccine or cure, the solution to it would be to follow strict quarantine. Governments from around the world have focused on the containment of the virus with varying degrees of success. Certain countries maintaining a low mortality rate are worth praise, and a detailed study of these efforts would benefit other countries to fight the virus. The use of technology and its integration into crucial strategies in fighting the deadly disease have proven beneficial on many fronts. Technology is being used to tackle unavoidable circumstances that may have arisen but put people at risk. Technologies that minimize human contact and can be remotely controlled reduce the risk of virus transmission from one another. The study aims to identify some remote technologies that have proved beneficial in the fight against the deadly Corona virus.Keywords
COVID-19, Robotics, Remote Access, Automation.Full Text
References
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- Agricultural Mobile Robots in Weed Management and Control
Abstract Views :104 |
PDF Views:0
Authors
Affiliations
1 Hobby Researcher in Robotics, Artificial Intelligence, IoT, US
2 Cambridge Institute of Technology, Bangalore, IN
3 Faculty, Facilitator, LeenaBOT Robotics, NG
4 Student, LeenaBOT Robotics, Bangalore, IN
1 Hobby Researcher in Robotics, Artificial Intelligence, IoT, US
2 Cambridge Institute of Technology, Bangalore, IN
3 Faculty, Facilitator, LeenaBOT Robotics, NG
4 Student, LeenaBOT Robotics, Bangalore, IN
Source
International Journal of Advanced Networking and Applications, Vol 13, No 3 (2021), Pagination: 5001-5006Abstract
The introduction of various robotics technology has made it easier to apply these approaches to agricultural procedures. However, due to the enormous differences in shape, size, rate and type of growth, kind of yield, and environmental needs for different types of crops, implementing this technology on farms has proven difficult. Agricultural processes are a series of time-dependent, methodical, repeated actions. Tilling, soil analysis, seeding, transplanting, crop scouting, insect management, weed removal, and harvesting are all major processes in open arable farming, and robots can help with all of them. By shrinking the range of the search grayscale range, the new method efficiently shortens the algorithm's search speed and reduces computation processing time. The edge contour picture of the corn and weed targets is used as the study object, and we built an algorithm to achieve an accurate selection of the 2D coordinate points of the corn and weed targets in the field crop image. A quadratic traversal algorithm is proposed in this paper for selecting target 2D coordinate points in the pixel coordinate system, as well as the related traversal search box. To achieve real-time target recognition and complete automatic cut classification of targets, the Faster R-CNN deep network model based on the VGG-16 feature extraction network is deployed. The use and implementation of our ideas in this study can help intelligent weeding robots perform more precise weeding operations and increase their efficiency.Keywords
Agricultural Robotics, Deep Learning, LeenaBOT, Weeding Robot.Full Text
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