Saving the Earth with Applied Ai
Earth Day was created to draw attention to how we can make the world a better place. At ElectrifAi, we help improve the world through the power of practical artificial intelligence (Ai) and pre-built machine learning (ML) models.
How? By using the accumulated data we have on our planet.
Let’s discuss three use cases based on the conversations we’ve been having around the producer, grower, and agricultural side of Ai. You’ll see how you can harness data and turn it into something we can use to make better decisions.
Ai Enhances Agriculture Viability
There are a lot of things growers can do to increase the viability of their product. And that ability is increased dramatically by adding Ai.
Applied Ai in computer vision is a very useful tool for agriculture. We can take past data on things that have been working and use that to change how we do things in the future. Such as changing the predictive maintenance on production lines.
For example, say you grow fruit in Latin America. There are certain conditions that must be met to successfully grow the fruit and have it stay fresh by the time it is sold at the store.
Computer vision can precisely target the exact maturity level of the fruit in each stage of growing, picking, and shipping. Really understanding the fruit’s lifecycle will determine if the fruit should be shipped far away or sold more locally. Determining new areas of where to ship the fruit ensures less food is wasted.
Many growers can look with their eyes to say if a piece of fruit is good or not good and pick it out of a line. By using computer vision, however, the ingenuity of those individuals can be increased to not only identify bad fruit but determine how long the fruit will last and make better decisions about where to sell it.
Increasing the efficiency of growers can ultimately give more food to people and create more supply for those who need it. Less food is wasted with the power of Ai.
Ai Optimizes Soil and Hydroponics
Both soil and water (hydroponics) have benefits but also drawbacks to growing food.
IoT plays a huge part in improving the planet. Electronic sensors are used to understand both soil and water. The data from those sensors can help us make better decisions, such as checking the pH level of the soil, what we plant, how long we keep it there, quality of the water, quality of light, etc.
We have so many ways of taking data from the planet and using that data to help successfully grow food. This makes food easier to grow and produces more of it. Data from the sensors can also help create more efficiencies and drive insights into the data that can help improve the planet’s resources.
Ai Preserves Food Integrity
Previously, applesauce was sold in cups with tin foil lids. The industry has evolved, however, so you don't see much of those anymore. Now, there are pouches of applesauce that better preserve the integrity of the product.
Do you ever think about how the containers are manufactured? A lot goes into creating the pouch and sealing it. There are companies that specialize in producing these items.
How do we make those companies and their processes better? How can we detect failure before it even happens? By using intelligent failure discovery.
If we could discover failure before it occurs, we can avoid it before the failure happens. Patterns in data determine where something is likely to fail. Using those patterns to prevent future occurrences of failure from happening to improve the process and the integrity of the product.
There are many initiatives in progress that are trying to make the world a better place. There are open data sets that can become a project you can work on. When you have the right data, many technologies can help you build your project.
Computer vision, for example, uses cognitive services to build on top of an existing model that knows what a specific object looks like (e.g., conveyor belts, greenhouses, etc.). You can upload as little as 20 images of anything and custom train that model to specifically see what you’d like it to identify.
But if you need even more customization, ElectrifAi can help!
Using someone else’s data and machine learning model to try and solve your business problem will only get you so far (such as using black box machine learning models that have preset configurations and are not customizable).
You could also create your own machine learning models but you’d have to deal with the headache of building something from scratch that could take months or years and never result in anything useful.
What if you could take a machine learning model someone has already built and customize it with your own data? That’s the meet in the middle called applied Ai or Machine Learning as a Service (MLaaS). That’s what ElectrifAi does … and does well!
Today's technology is incredible. We’re taking data harnessed from the environment and combining that with algorithms proven to work solving problems and getting them to talk to each other. That’s the real power of saving the earth with applied Ai.
We’ve talked with many companies who don’t have those capabilities, however, so why not leverage the benefits of MLaaS! Contact us today to find out more.
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