Design of Automated Seed Sowing Robot for BT Cotton Seed

Nagdeve, Tanmay; Jangde, Pranay; Tandulkar, Hrushikesh; Dhara, Sushobhit; Ukani, Neema; Chakole, Saurabh

doi:10.1109/icirca48905.2020.9183259

Cited by 9 publications

(2 citation statements)

References 3 publications

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“…Design of automated seed sowing robot for BT cotton seed [40] Fog computing -based seed sowing robots for agriculture [41] Using a cleverly built mechanical mechanism, this technology totally automates the seed sowing procedure. As the seeds are sown, this robot decreases the work and total cost of sowing.…”

Section: Referencementioning

confidence: 99%

Microcontroller Implementation in Precision Planting: A Review

Beg,

Chauhan

2024

AJAAR

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Precision farming, also known as precision agriculture, is a crop management method that optimizes agricultural production by utilizing technology and data for precise placement of seed, fertilizer and pesticides. It enhances increase crop yields, reduce waste, and reduce environmental impact by applying the appropriate amount of inputs, such as seed, water, fertilizer, and pesticides for each crop. Farmers can reduce expenses by reducing the usage of expensive inputs while increasing yields and crop quality by employing precision farming techniques. Commercially available planters normally use mechanical metering systems which have many limitations including, skidding of the wheel, non-uniform seed rate, wastage of the seed and higher maintenance cost. It is evident from recent researchers that irregularly in seed placement, which is generally caused due to wheel slippage and seed metering systems powered by electric or hydraulic motor can maintain accurate seed placement and can work at higher speeds compared to traditional planters.

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Section: Referencementioning

confidence: 99%

Microcontroller Implementation in Precision Planting: A Review

Beg,

Chauhan

2024

AJAAR

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“…Of the three tasks, sowing of one individual seed has not been realized, especially in a dense plant environment [32][33][34][35][36]. The ideal farm conditions for Synecoculture are those where the topsoil is not exposed, and various vegetation is always overgrown.…”

Section: Relevant Researchmentioning

confidence: 99%

Agricultural Robot under Solar Panels for Sowing, Pruning, and Harvesting in a Synecoculture Environment

et al. 2022

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Currently, an agricultural method called SynecocultureTM has been receiving attention as a means for multiple crop production and recovering from environmental degradation; it helps in regreening the environment and establishing an augmented ecosystem with high biodiversity. In this method, several types of plants are grown densely, and their management relies mainly on manual labor, since conventional agricultural machines and robots cannot be applied in complex vegetation. To improve work efficiency and boost regreening by scaling-up Synecoculture, we developed a robot that can sow, prune, and harvest in dense and diverse vegetation that grows under solar panels, towards the achievement of compatibility between food and energy production on a large scale. We adopted a four-wheel mechanism with sufficient ability to move on uneven terrain, and a two orthogonal axes mechanism with adjusted tool positioning while performing management tasks. In the field experiment, the robot could move straight on shelving slopes and overcome obstacles, such as small steps and weeds, and succeeded in harvesting and weeding with human operation, using the tool maneuver mechanism based on the recognition of the field situation through camera image.

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Contribution of robotics in smart farming: A review

Wakchaure,

Patle

2024

AIP Conference Proceedings

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Design of Automated Seed Sowing Robot for BT Cotton Seed

Cited by 9 publications

References 3 publications

Microcontroller Implementation in Precision Planting: A Review

Microcontroller Implementation in Precision Planting: A Review

Agricultural Robot under Solar Panels for Sowing, Pruning, and Harvesting in a Synecoculture Environment

Contribution of robotics in smart farming: A review

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