2021 Research Projects
Projects are posted below; new projects will continue to be posted. To learn more about the type of research conducted by undergraduates, view the archived symposium booklets and search the past SURF projects.
This is a list of research projects that may have opportunities for undergraduate students. Please note that it is not a complete list of every SURF project. Undergraduates will discover other projects when talking directly to Purdue faculty.
You can browse all the projects on the list or view only projects in the following categories:
IoT for Precision Agriculture (4)
IoT4Ag P1: Autonomous recharging of ground and aerial mobile agricultural robot platforms
Description:
By 2050, the US population is estimated to grow to 400 million and the world population to 9.7 billion. Current agricultural practices account for 70% of global water use, energy accounts for one of the largest costs on a farm, and inefficient use of agrochemicals is altering Earth’s ecosystems. With finite arable land, water, and energy resources, ensuring food, energy, and water security will require new technologies to improve the efficiency of food production, create sustainable approaches to supply energy, and prevent water scarcity.
A new Engineering Research Center on the Internet of Things for Precision Agriculture (IoT4Ag) has recently been established to ensure food, energy, and water security by advancing technology to increase crop production, while minimizing the use of energy and water resources and the impact of agricultural practices on the environment. The center will create novel, integrated systems that capture the microclimate and spatially, temporally, and compositionally map heterogeneous stresses for early detection and intervention to better outcomes in agricultural crop production. The Center will create internet of things (IoT) technologies to optimize practices for every plant; from sensors, robotics, and energy and communication devices to data-driven models constrained by plant physiology, soil, weather, management practices, and socio-economics. We are looking to hire a cohort of SURF students to work on different activities in the center.
IoT4Ag 1: Autonomous recharging of ground and aerial mobile agricultural robot platforms
# students: 2 - US Citizens or permanent residents only
In this project, students will be tasked to design and implement an autonomous battery recharging system for ground and aerial mobile agricultural robot platforms.
Student 1:
Survey of state of the art - robot battery swapping systems
Mechanical design of battery swapping system - on robot/at charging station
Research and implement robot path planning to charging nearest charging station
Develop and test visual servoing algorithms for robot to dock in charging station
Student 2:
Survey of state of the art - wireless charging techniques
Waveform design for wireless charging
Proof of concept demonstration of candidate system(s)
Electrical system design/specifications for robot-side wireless charging system
A new Engineering Research Center on the Internet of Things for Precision Agriculture (IoT4Ag) has recently been established to ensure food, energy, and water security by advancing technology to increase crop production, while minimizing the use of energy and water resources and the impact of agricultural practices on the environment. The center will create novel, integrated systems that capture the microclimate and spatially, temporally, and compositionally map heterogeneous stresses for early detection and intervention to better outcomes in agricultural crop production. The Center will create internet of things (IoT) technologies to optimize practices for every plant; from sensors, robotics, and energy and communication devices to data-driven models constrained by plant physiology, soil, weather, management practices, and socio-economics. We are looking to hire a cohort of SURF students to work on different activities in the center.
IoT4Ag 1: Autonomous recharging of ground and aerial mobile agricultural robot platforms
# students: 2 - US Citizens or permanent residents only
In this project, students will be tasked to design and implement an autonomous battery recharging system for ground and aerial mobile agricultural robot platforms.
Student 1:
Survey of state of the art - robot battery swapping systems
Mechanical design of battery swapping system - on robot/at charging station
Research and implement robot path planning to charging nearest charging station
Develop and test visual servoing algorithms for robot to dock in charging station
Student 2:
Survey of state of the art - wireless charging techniques
Waveform design for wireless charging
Proof of concept demonstration of candidate system(s)
Electrical system design/specifications for robot-side wireless charging system
Research categories:
IoT for Precision Agriculture, Other
Preferred major(s):
ME, ECE, CS
Desired experience:
Student 1: upperclassman in mechanical engineering or equivalent program; experience with mechatronics, image processing, robotics, programming
Student 2: upper level student in electrical and computer engineering or equivalent, experience with battery systems
School/Dept.:
Mechanical Enginering
Professor:
David
Cappelleri
More information: iot4ag.us
IoT4Ag P2: IsoBlue integration to UGV/UAV platforms
Description:
By 2050, the US population is estimated to grow to 400 million and the world population to 9.7 billion. Current agricultural practices account for 70% of global water use, energy accounts for one of the largest costs on a farm, and inefficient use of agrochemicals is altering Earth’s ecosystems. With finite arable land, water, and energy resources, ensuring food, energy, and water security will require new technologies to improve the efficiency of food production, create sustainable approaches to supply energy, and prevent water scarcity.
A new Engineering Research Center on the Internet of Things for Precision Agriculture (IoT4Ag) has recently been established to ensure food, energy, and water security by advancing technology to increase crop production, while minimizing the use of energy and water resources and the impact of agricultural practices on the environment. The center will create novel, integrated systems that capture the microclimate and spatially, temporally, and compositionally map heterogeneous stresses for early detection and intervention to better outcomes in agricultural crop production. The Center will create internet of things (IoT) technologies to optimize practices for every plant; from sensors, robotics, and energy and communication devices to data-driven models constrained by plant physiology, soil, weather, management practices, and socio-economics. We are looking to hire a cohort of SURF students to work on different activities in the center.
IoT4Ag P2: IsoBlue integration to UGV/UAV platform
# students: 1, US Citizens or permanent residents only
In this project, the student will be tasked with system architecture design, integration, and mechanical design for an integrated IsoBlue communications module with existing UGV and UAV platforms. IsoBlue is an on-going project for an open source telematics and edge computing device, which connects to the CANbus of agricultural machines in order to read and log machine sensors and to create the capability for machine control. IsoBlue is also a general purpose sensor hub capable of communications using WiFi, Bluetooth Low Energy, TV whitespaces, and LoRa and it creates a bridge to the cloud using LTE cellular.
The ECE student on this project will:
Survey the state of the art in telematics, edge computing, and sensor networking
Specify the electrical and mechanical interfaces needed to integrate with the UGV platform
Modify the existing IsoBlue design to implement IsoBlue/UGV integration
A new Engineering Research Center on the Internet of Things for Precision Agriculture (IoT4Ag) has recently been established to ensure food, energy, and water security by advancing technology to increase crop production, while minimizing the use of energy and water resources and the impact of agricultural practices on the environment. The center will create novel, integrated systems that capture the microclimate and spatially, temporally, and compositionally map heterogeneous stresses for early detection and intervention to better outcomes in agricultural crop production. The Center will create internet of things (IoT) technologies to optimize practices for every plant; from sensors, robotics, and energy and communication devices to data-driven models constrained by plant physiology, soil, weather, management practices, and socio-economics. We are looking to hire a cohort of SURF students to work on different activities in the center.
IoT4Ag P2: IsoBlue integration to UGV/UAV platform
# students: 1, US Citizens or permanent residents only
In this project, the student will be tasked with system architecture design, integration, and mechanical design for an integrated IsoBlue communications module with existing UGV and UAV platforms. IsoBlue is an on-going project for an open source telematics and edge computing device, which connects to the CANbus of agricultural machines in order to read and log machine sensors and to create the capability for machine control. IsoBlue is also a general purpose sensor hub capable of communications using WiFi, Bluetooth Low Energy, TV whitespaces, and LoRa and it creates a bridge to the cloud using LTE cellular.
The ECE student on this project will:
Survey the state of the art in telematics, edge computing, and sensor networking
Specify the electrical and mechanical interfaces needed to integrate with the UGV platform
Modify the existing IsoBlue design to implement IsoBlue/UGV integration
Research categories:
IoT for Precision Agriculture, Other
Preferred major(s):
ECE or CS
Desired experience:
ECE or CS with background in embedded systems with C programming
School/Dept.:
ECE
Professor:
James
Krogmeier
More information: oatscenter.org
IoT4Ag P3: Biophysical modeling and integration with in-situ and remotely sensed data
Description:
By 2050, the US population is estimated to grow to 400 million and the world population to 9.7 billion. Current agricultural practices account for 70% of global water use, energy accounts for one of the largest costs on a farm, and inefficient use of agrochemicals is altering Earth’s ecosystems. With finite arable land, water, and energy resources, ensuring food, energy, and water security will require new technologies to improve the efficiency of food production, create sustainable approaches to supply energy, and prevent water scarcity.
A new Engineering Research Center on the Internet of Things for Precision Agriculture (IoT4Ag) has recently been established to ensure food, energy, and water security by advancing technology to increase crop production, while minimizing the use of energy and water resources and the impact of agricultural practices on the environment. The center will create novel, integrated systems that capture the microclimate and spatially, temporally, and compositionally map heterogeneous stresses for early detection and intervention to better outcomes in agricultural crop production. The Center will create internet of things (IoT) technologies to optimize practices for every plant; from sensors, robotics, and energy and communication devices to data-driven models constrained by plant physiology, soil, weather, management practices, and socio-economics. We are looking to hire a cohort of SURF students to work on different activities in the center.
IoT4Ag P3: Biophysical modeling and integration with in-situ and remotely sensed data
# of students: 3, US Citizens or permanent residents only
This interdisciplinary project will focus on acquisition and processing of remotely sensed data acquired by sensors on UAVs and wheel-based vehicles, developing empirical models, and working collaboratively with teams in the College of Agriculture to integrate empirical machine learning models with biophysical modeling to detect plant stress and predict yield. The project will provide opportunities for students to learn about sensors via field-based data acquisition from remote sensing platforms, expand their understanding of techniques for processing data, use data products for applications related to cropping systems (plant breeding, production management, in-season treatments) and engage in development of hybrid models that include both data analytics and biophysically based approaches. Use of existing models may require use of APIs for data acquisition, familiarity with file types, and aptitude for functions and systems thinking.
The project will involve both field-based and computer laboratory focused research. Courses /experience in python programming, data analytics and image processing, and particularly related to remote sensing technologies, are desirable. Interest in interdisciplinary research is essential.
A new Engineering Research Center on the Internet of Things for Precision Agriculture (IoT4Ag) has recently been established to ensure food, energy, and water security by advancing technology to increase crop production, while minimizing the use of energy and water resources and the impact of agricultural practices on the environment. The center will create novel, integrated systems that capture the microclimate and spatially, temporally, and compositionally map heterogeneous stresses for early detection and intervention to better outcomes in agricultural crop production. The Center will create internet of things (IoT) technologies to optimize practices for every plant; from sensors, robotics, and energy and communication devices to data-driven models constrained by plant physiology, soil, weather, management practices, and socio-economics. We are looking to hire a cohort of SURF students to work on different activities in the center.
IoT4Ag P3: Biophysical modeling and integration with in-situ and remotely sensed data
# of students: 3, US Citizens or permanent residents only
This interdisciplinary project will focus on acquisition and processing of remotely sensed data acquired by sensors on UAVs and wheel-based vehicles, developing empirical models, and working collaboratively with teams in the College of Agriculture to integrate empirical machine learning models with biophysical modeling to detect plant stress and predict yield. The project will provide opportunities for students to learn about sensors via field-based data acquisition from remote sensing platforms, expand their understanding of techniques for processing data, use data products for applications related to cropping systems (plant breeding, production management, in-season treatments) and engage in development of hybrid models that include both data analytics and biophysically based approaches. Use of existing models may require use of APIs for data acquisition, familiarity with file types, and aptitude for functions and systems thinking.
The project will involve both field-based and computer laboratory focused research. Courses /experience in python programming, data analytics and image processing, and particularly related to remote sensing technologies, are desirable. Interest in interdisciplinary research is essential.
Research categories:
Big Data/Machine Learning, IoT for Precision Agriculture, Other
Preferred major(s):
ABE, CE, ECE, IE
Desired experience:
Courses /experience in python programming, data analytics and image processing, and particularly related to remote sensing technologies, are desirable.
Strong computer and math skills, preferably experience with data wrangling and visualization (Python preferred)
Interest in interdisciplinary research is essential.
School/Dept.:
CE, ECE, Agronomy
Professor:
Melba
Crawford
More information: iot4ag.us
IoT4Ag P4: Frontiers in Thermal Stress Sensing
Description:
By 2050, the US population is estimated to grow to 400 million and the world population to 9.7 billion. Current agricultural practices account for 70% of global water use, energy accounts for one of the largest costs on a farm, and inefficient use of agrochemicals is altering Earth’s ecosystems. With finite arable land, water, and energy resources, ensuring food, energy, and water security will require new technologies to improve the efficiency of food production, create sustainable approaches to supply energy, and prevent water scarcity.
A new Engineering Research Center on the Internet of Things for Precision Agriculture (IoT4Ag) has recently been established to ensure food, energy, and water security by advancing technology to increase crop production, while minimizing the use of energy and water resources and the impact of agricultural practices on the environment. The center will create novel, integrated systems that capture the microclimate and spatially, temporally, and compositionally map heterogeneous stresses for early detection and intervention to better outcomes in agricultural crop production. The Center will create internet of things (IoT) technologies to optimize practices for every plant; from sensors, robotics, and energy and communication devices to data-driven models constrained by plant physiology, soil, weather, management practices, and socio-economics. We are looking to hire a cohort of SURF students to work on different activities in the center.
IoT4Ag P4: Frontiers in Thermal Stress Sensing
2 students - US Citizens or permanent residents only
Crop canopy temperatures are modulated by transpiration of water vapor from leaf surfaces when water exits via leaf stomata. Although thermal sensors are being deployed on drones and autonomous robots, too little is known about the relationship between evaporative cooling and stomatal conductance that can be measured directly via leaf photosynthesis assessment (e.g. with a LiCor 6400 or 6800 portable photosynthesis system) . The simultaneous and direct measurement of thermal properties of corn canopies from above the canopy and below the canopy is suggested here to coincide with leaf photosynthesis measurements. The project goal is to investigate the differential between air temperatures and both upper and lower leaf temperatures via both thermal sensors and leaf stomatal conductance assessment for corn plots under a range of water deficit conditions. Knowing these relationships could help guide the timing (diurnal and weekly frequency) for thermal canopy assessments at different growth stages. Field experiments will be established in spring 2021 at the Agronomy Center for Research and Education. Corn treatments may include both hybrid and management variables intended to create a spectrum of crop water stress. Corn biomass measurements will also be taken to study crop growth rates occurring in the actual range of “water productivity” treatments.
A new Engineering Research Center on the Internet of Things for Precision Agriculture (IoT4Ag) has recently been established to ensure food, energy, and water security by advancing technology to increase crop production, while minimizing the use of energy and water resources and the impact of agricultural practices on the environment. The center will create novel, integrated systems that capture the microclimate and spatially, temporally, and compositionally map heterogeneous stresses for early detection and intervention to better outcomes in agricultural crop production. The Center will create internet of things (IoT) technologies to optimize practices for every plant; from sensors, robotics, and energy and communication devices to data-driven models constrained by plant physiology, soil, weather, management practices, and socio-economics. We are looking to hire a cohort of SURF students to work on different activities in the center.
IoT4Ag P4: Frontiers in Thermal Stress Sensing
2 students - US Citizens or permanent residents only
Crop canopy temperatures are modulated by transpiration of water vapor from leaf surfaces when water exits via leaf stomata. Although thermal sensors are being deployed on drones and autonomous robots, too little is known about the relationship between evaporative cooling and stomatal conductance that can be measured directly via leaf photosynthesis assessment (e.g. with a LiCor 6400 or 6800 portable photosynthesis system) . The simultaneous and direct measurement of thermal properties of corn canopies from above the canopy and below the canopy is suggested here to coincide with leaf photosynthesis measurements. The project goal is to investigate the differential between air temperatures and both upper and lower leaf temperatures via both thermal sensors and leaf stomatal conductance assessment for corn plots under a range of water deficit conditions. Knowing these relationships could help guide the timing (diurnal and weekly frequency) for thermal canopy assessments at different growth stages. Field experiments will be established in spring 2021 at the Agronomy Center for Research and Education. Corn treatments may include both hybrid and management variables intended to create a spectrum of crop water stress. Corn biomass measurements will also be taken to study crop growth rates occurring in the actual range of “water productivity” treatments.
Research categories:
IoT for Precision Agriculture, Other
Preferred major(s):
Agronomy, Botany, or other plant science field; CE/ECE
Desired experience:
Background in Agronomy, Botany, or other plant science field
CE/ECE with background in sensor-based data acquisition
School/Dept.:
Agronomy
Professor:
Tony
Vyn
More information: iot4ag.us