There is no denying the fact that AI is here and here to stay. Many companies all over the globe have already included AI to their work, and many more are getting added in that list. Agriculture is no stranger to AI, Microsoft and ICRISAT have already been helping farmers in India with their crop, helping farmers to save their crop from pest attacks and the right time to sow the seeds based on weather condition. Now IBM has developed a paper testing strip that when combined with a mobile app, relies on machine vision to measure the precise amounts of chemicals in samples of water and soil.
While earlier farmers had to send their samples of soil and water to the lab to get them tested, which was a lengthy process and at times took so long that the results are no longer justify the actual quality of the soil and water. On one hand it was lengthy and a process that took time on the other hand the process was costly for most of the farmers.
Now IBM researcher have found a way that will help farmer in Brazil fight this testing problem, the AI technology is still a prototype but is able to help the farmers to easily conduct the chemical analyses and at that very moment. IBM's Mathias Steiner wrote in his blog post that "the prototype could revolutionize digital agriculture and environmental testing." The AI could have a major impact on the small farms and the food they produce.
What is it?
The IBM technology is called AgroPad and is a paper device about the size of a business card. The AgroPads can be personalized according to a farmer according to his needs. How it works is that, the technology has microfluidics chip inside it which are able to perform chemical analysis of water or soil samples in around 10 seconds or less. All the farmers have to do is put the sample of soil or water on the card and on the other side a set of circles provides colorimetric test results. The farmer can then use a dedicated application that will provide them with immediate and accurate results.
Translating the colour composition and intensity into chemical concentrations the app uses machine vision to do so. These results have been more reliable than those that rely on human visions. The technology in its prototype stage is able to measure the pH, aluminium, chlorine, magnesium and nitrogen dioxide, but the research team has made it clear that is currently working on extending the library of chemical indicators
According to Steiner's blog, "Once the test results are in, the data can be streamed to the cloud and labelled with a digital tag to mark the time and location of the analysis. Results for millions of individual tests could be stored."