Without the agricultural industry and its farmers, we would not have access to the delicious variety of fruits, vegetables, and meats that make for memorable meals. Agriculture, like many other major industries, has been significantly influenced by technology. Let’s examine in detail how big data contributes to changes in agricultural practices.
Drone-Distributed Sensors Monitor Crop Conditions
A research team at the King Abdullah University of Science and Technology (KAUST) in Saudi Arabia has devised methods for inspecting the characteristics of crops by dropping sensors from drones. One of the devices is a stretchable sensor that monitors plant growth changes to the micrometer level.
The other is called a PlantCopter, and it measures temperature and humidity as it spirals through the air in a corkscrew pattern. In most cases, its design allows it to adhere naturally to leaves and other plant parts. Even if a PlantCopter fails to attach to a crop, the system is cost-effective enough that such an outcome is not prohibitively expensive, according to the project’s creators.
Other commercially available monitoring systems require manual placement of equipment, and sensors frequently do not communicate with one another. If they have communication capabilities, the cost of these systems increases significantly.
In this new configuration, sensors transmit data for an average of 151 days. The collected data is then transmitted to nearby drones or smartphone users who can analyze the information and make any necessary adjustments to farming techniques. The ability to view such detailed metrics in a streamlined manner saves farmers time, labor, and money.
Foresight Modeling Helps Farmers Anticipate the Future
A consistent aspect of farming is that it is fraught with danger. Farmers may spend a substantial amount of money on crops that do not perform as expected, or they may experience severe droughts with negative and lasting effects. Obviously, it is impossible to predict the future with absolute certainty, but some experts believe that big data could improve our ability to foresee the future.
Scientists who specialize in integrated modeling at International Center for Tropical Agriculture (CIAT), a CGIAR-affiliated research center, could make groundbreaking advances. CGIAR is a global partnership of individuals working toward food security in the future. CIAT addresses hunger, poverty, and nutrition by increasing the efficiency of agricultural systems.
Decision and Policy Analysis (DAPA) is a division of CIAT that uses integrated modeling techniques to calculate the impact of climate change and water resources on agriculture using foresight scenarios. It employs mathematics to predict the plausibility of potential outcomes, such as if certain factors remain constant while others, such as the rate of technology adoption in agriculture, change.
Artificial intelligence (AI) can perform certain tasks better than humans, including image analysis and disease diagnosis. This is partially due to the efficiency and precision with which it operates. Similar to other applications of integrated modeling, this one provides results more quickly than humans could without technology. In addition, the results aid farmers in making informed investment decisions.
Real-Time Livestock Health Tracking Could Reduce Widespread Illnesses
Any farmer who has ever witnessed a fatal disease ravage a herd of livestock knows how devastating it is to suddenly lose a significant percentage of cattle from a previously healthy herd. Despite the best efforts of those caring for the animals, it is not always possible to recognize the symptoms of diseases early enough to prevent fatalities.
Nonetheless, a trial in New South Wales, Australia, may pave the way for a healthier future for livestock. About 10,000 cattle in New South Wales will receive Bluetooth-enabled ear tag monitors with a range of approximately 300 meters.
By utilizing readers that interpret the data transmitted by the monitoring devices, farmers could receive earlier warnings of potential diseases and more precise health indicators. All collected data is stored in the cloud, enabling straightforward analysis in the future. In addition, farmers can receive mobile alerts regarding individual animals that may be in distress based on biometric data, such as grazing patterns.
The chief executive officer of HerdDogg, the company that developed the tracking system, notes that this technology is less expensive than other alternatives for the beef industry. In addition to improving animal welfare, it may also reduce labor costs.
Data Analysis Facilitates Multiple Benefits
The preceding examples provide a fascinating overview of ways to apply big data to farming that could radically alter the livelihoods of farmers and the agriculture industry. Some of the aforementioned initiatives are still in their infancy, but the scientists involved are eager to experiment with new methods of implementing the technology. Consequently, future pairings of agriculture and big data should yield benefits that have yet to be discovered.