Advancements in Industry-Agriculture 5.0: Utilizing Unmanned Ground and Aerial Vehicles for Sustainable Precision Agriculture

Bogrekci, Ismail; Demircioglu, Pinar

doi:10.14313/jamris-2025-034

Figures & Tables

Thermal measurements and their results in vineyards [7,25]

Isometric and Three-Dimensional View of the Wheeled Robot Platform

Circuit for Controlling Two Motors for Locomotion

Determination of Agricultural Land [Safar]

Drawing and Defining Field Boundaries [Safar]

Determination of the Route, Adding Robots and Equipment [Safar]

System Operation Through Integration [Safar]

Office-Based Testing of Distance Measurement Using Stereo Imaging

Results of Topography Determination Using Stereo Imaging Studies

RTK-GPS Route Determination and Planning Study

Simulation of Robot Maneuvering on RTK-GPS Route Determination and Planning

Simulation of Robot Maneuvering on RTK-GPS Route Determination and Planning - Route Numbers

Location Images of the Manisa Viticulture Research Station

Figure 20.

Profile Probe

The design of the robot platform, its center of gravity, and dimensional specifications

Dynamical Simulation Results of the Robot (Power)

Dynamical Simulation Results of the Robot (Energy)

Dynamical Simulation Results of the Robot (Motor Force)

Static Analysis Results of the Robot (Stress)

Static Analysis Results of the Robot (Displacement)

Static Analysis Results of the Robot (Strain)

Dynamic Analysis Results of the Robot (Stress)

Dynamic Analysis Results of the Robot (Displacement)

Dynamic Analysis Results of the Robot (Strain)

The version operated with improved detection cards for calipers and ultrasonic sensors

RTK-GPS to be used for guiding the robot

Google Maps output (37°51’24.7”N 27°51’29.8”E 37.856858, 27.858279)

Vineyard robot detection and control software

Vineyard robot detection and control software - Sensor data

Lidar measurement - Unobstructed conditions

Lidar measurement - Obstructed conditions

Lidar measurement - Two obstacles present

Comparison of Precision Farming and Conventional Farming Practices

Feature	Precision Farming	Conventional Farming
Efficiency	Increased efficiency through tech	Lower efficiency
Resource Conservation	Minimizes resource overuse	Resource-intensive
Data-Driven Decision-Making	Informed decisions through data analysis	Experience-based decisions
Labor Requirements	Reduced labor needs (automation)	Labor-intensive
Environmental Impact	Reduced environmental impact	Environmental concerns
Initial Costs	Higher initial costs	Lower initial costs
Complexity	Complex data management	Simplicity and familiarity
Sustainability	Enhanced sustainability	Reduced sustainability

Comparison of UAVs and UGVs in Agricultural Farm Operations

Depth (cm)	Saturation (%)	Texture	Total Salinity (%)	PH	CaCO₃(%)	Total N (%)
0–30	30.00	Sandy	0.0113	7.80	5.60	0.11
30–60	31.00	Loamy	0.0159	7.87	4.80	0.11
60–90	37.00	Loamy	0.0282	7.88	8.00	0.09
Condition			Non-Saline	Slightly Alkaline	High	Medium

Location Data Comparison Table

	Single Point Position (SPP) location data obtained with Piksi RTK GPS	Location data obtained using Google Maps
Latitude (Decimal)	37.8568583853	37.856858
Longitude (Decimal)	27.8582785723	27.858279
Latitude (Degrees Minutes Seconds)	37° 51’24.6902” N	37° 51’ 24.7” N
Longitude (Degrees Minutes Seconds)	27° 51’29.8029” E	27° 51’ 29.8” E
Distance between the two acquired points (Decimal)	0,00000039	-0,00000043
Distance between the two acquired points (Degrees Minutes Seconds)	0° 0’0.0014” N	0° 0’ 0.0015” W
Distance between the two acquired points (Meters)	0.06455 m

Open Data Resources in the Field of Smart Agriculture [6]

Data Source	Description
USDA National Agricultural Statistics Service (NASS) Data	Crop production, livestock statistics, and agricultural information in the United States
European Space Agency’s Sentinel Data	High-resolution satellite imagery for crop monitoring and land use
NOAA Climate Data	Weather and climate data, including forecasts, rainfall, and temperature
Global Open Data for Agriculture and Nutrition (GODAN)	Open datasets related to agriculture, food security, and nutrition
NASA Earthdata	Remote sensing data for monitoring climate, soil moisture, and vegetation
FAO Data	Agricultural data and information on global food production and trade
IoT Sensor Data	Sensor data, such as soil moisture and temperature, from IoT devices in fields
Crop and Soil Databases	Information on crop yields, soil quality, and nutrient levels
Agricultural Research Institutions	Data from research institutions on crop trials, pest monitoring, and experiments
OpenWeatherMap	Weather data, including current conditions, forecasts, and historical records
Government Agricultural Portals	Information on farming practices, subsidies, and agricultural policies
Community-Generated Data	User-generated data sharing experiences, practices, and insights

Advancements in Industry-Agriculture 5.0: Utilizing Unmanned Ground and Aerial Vehicles for Sustainable Precision Agriculture

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Comparison of Precision Farming and Conventional Farming Practices

Comparison of UAVs and UGVs in Agricultural Farm Operations

Location Data Comparison Table

Open Data Resources in the Field of Smart Agriculture [6]