Bug-like features allow researchers to gather data from sunlight to enhance solar energy, landscape architecture, farming, and other industries.
Pennsylvania State University associate professor of energy and mineral engineering Jeffrey Brownson said in the solar industry, people measure the power potential of sunlight, which is important for energy production.
Brownson said: "But very few people are using sunlight for information, and this baseline data could help improve a number of industries. If you can start collecting the right information, you can use it to inform crop yields, assess fire risk of sloped surfaces such as mountains, and predict home heating patterns and solar energy generation."
According to Brownson, that information is missing now as existing technology to capture sunlight’s directionality on a regular basis takes lot of investment.
A pyrheliometer can measure the angle of direct sunlight accurately, but it commonly costs between $20,000 and $30,000. The device also includes moving parts that can break, and it should be maintained regularly.
Due to the disadvantages of the device, the team at the Penn State wanted to come up with a new device with reduced cost. The team also includes Vivek Srikrishnan and George Young .
A prototype version is completed and they called it the All-Seeing EYE (ASE). With the help of seed grant from the Penn State Institute of Energy and the Environment, the team has installed 2 devices in Central Pennsylvania.
The team says that it got the idea for the device when they investigating power generated by sunlight or solar irradiance, needed to heat buildings.
One of the team members, Vivek Srikrishnan explains, a person standing in the sun in summer will get hotter than a person standing in shade. The same heating should affect heating in building as well.
The team came to a conclusion that there was a flaw in standard way solar irradiance is measured.
The device has been designed to measured sunlight coming in from different directions. On a typical sunny day, the sunlight is mixed with light coming in directly from the sun and other light which has been absorbed, reflected and scattered light.
With the device the team aims to track direct sunlight and filter out diffused and reflected sunlight. The device is cube-shaped and has many light sensors on all sides of its surface. But, even with many sensors, tracking only direct sunlight can be an insurmountable task. Which is the reason why, the team has plans to employ neural network artificial intelligence.
In order for the artificial intelligence to come up with anything conclusive, the team must be gather at least one year worth of data on direct sunlight, clouds and snowfall conditions.
Talking about the accuracy of the new device Vivek Srikrishnan said: "For all weather conditions, existing models to estimate direct sunlight had between 20 and 30 percent error. Ours had less than 10 percent error. In snowy conditions, existing models had a 48 percent error, while ours had 15 percent."
