TY - GEN
T1 - Devices, systems, and methods for automated monitoring enabling precision agriculture
AU - Das, Jnaneshwar
AU - Cross, Gareth
AU - Qu, Chao
AU - Makineni, Anurag
AU - Tokekar, Pratap
AU - Mulgaonkar, Yash
AU - Kumar, Vijay
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2015/10/7
Y1 - 2015/10/7
N2 - Addressing the challenges of feeding the burgeoning world population with limited resources requires innovation in sustainable, efficient farming. The practice of precision agriculture offers many benefits towards addressing these challenges, such as improved yield and efficient use of such resources as water, fertilizer and pesticides. We describe the design and development of a light-weight, multi-spectral 3D imaging device that can be used for automated monitoring in precision agriculture. The sensor suite consists of a laser range scanner, multi-spectral cameras, a thermal imaging camera, and navigational sensors. We present techniques to extract four key data products - plant morphology, canopy volume, leaf area index, and fruit counts - using the sensor suite. We demonstrate its use with two systems: multi-rotor micro aerial vehicles and on a human-carried, shoulder-mounted harness. We show results of field experiments conducted in collaboration with growers and agronomists in vineyards, apple orchards and orange groves.
AB - Addressing the challenges of feeding the burgeoning world population with limited resources requires innovation in sustainable, efficient farming. The practice of precision agriculture offers many benefits towards addressing these challenges, such as improved yield and efficient use of such resources as water, fertilizer and pesticides. We describe the design and development of a light-weight, multi-spectral 3D imaging device that can be used for automated monitoring in precision agriculture. The sensor suite consists of a laser range scanner, multi-spectral cameras, a thermal imaging camera, and navigational sensors. We present techniques to extract four key data products - plant morphology, canopy volume, leaf area index, and fruit counts - using the sensor suite. We demonstrate its use with two systems: multi-rotor micro aerial vehicles and on a human-carried, shoulder-mounted harness. We show results of field experiments conducted in collaboration with growers and agronomists in vineyards, apple orchards and orange groves.
UR - http://www.scopus.com/inward/record.url?scp=84952795509&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84952795509&partnerID=8YFLogxK
U2 - 10.1109/CoASE.2015.7294123
DO - 10.1109/CoASE.2015.7294123
M3 - Conference contribution
AN - SCOPUS:84952795509
T3 - IEEE International Conference on Automation Science and Engineering
SP - 462
EP - 469
BT - 2015 IEEE Conference on Automation Science and Engineering
PB - IEEE Computer Society
T2 - 11th IEEE International Conference on Automation Science and Engineering, CASE 2015
Y2 - 24 August 2015 through 28 August 2015
ER -