Yeah, Science: This Smart Tablecloth Can Suggest Meal Recipes Based on Food Ingredients Kept on it
Screengrab from video uploaded by ACM SIGCHI / YouTube.
How would it be if there was an app that could determine a recipe by recognising items on the table? That high tech makeover could be really nice. Well, some researchers at Microsoft teamed up with universities in the US to develop a smart fabric system called "Capacitivo". The low-cost ‘smart tablecloth’ developed by the scientist can sense foodstuff, beverage and other objects when placed on top of it.
Not only that, the smart cloth, based solely on touch, will also suggest meal prepping recipes. The fabric uses a fusion of machine learning and a capacitive electrode grid to ascertain the material as well as the shape of an object. The technology has been established by Microsoft with Dartmouth College, New Hampshire. The technique has been primed with a machine learning system to identify objects.
Microsoft researcher Teddy Seyed decoded the technology while speaking to the Telegraph. “It uses the basic principle of a touch screen that detects your finger,” he said.
As per scientists, the device successfully spotted 20 items in lab tests, including a grapefruit, as well as other objects like an Apple AirPods case, glasses, bowls and a bottle of hand sanitiser. When connected with a smart speaker such as Amazon Echo, the tablecloth can hand on recipe steps to the user. Capacitivo can also sense the amount of moisture in the soil and alert users when a plant needs to be watered.
Being an initial project, the system has limitations as it doesn’t mark metallic stuff and also square-edged items. Certain drinks that don’t have a clear capacitance footprint also don’t produce reliable results.
Scientists also believe Capacitivo as a memory tool as it could remind the user to clean up if they have left an empty food bowl. The team is hoping that in the near future they would be dealing with less-than-ideal placement, among other upgrades. It could give way to a seamless smart home where one doesn’t have to rely on clunky methods to perceive what’s in the kitchen.