衝繩開發金融公司

2023年6月26日

當您運行大現實工業操作,總有規或讀出的內心深處的設施,你的工程師或現場團隊需要檢查。Lilz日本創業,構建遠程設備你可以設置閱讀這些米,和該公司籌集了410萬美元,因為他們進入北美市場。這聽起來可能有點奇怪這個現代——為什麼不首先智能蒸汽壓力表嗎?簡單的事實是許多基礎設施和重工業沒有這個選項,或改造可能會非常昂貴。但是為了安全或效率的原因,一些簡單的讀出需要定期觀察。發送一個人類是最簡單的解決方案,或直到Lilz設備可用幾年前。堆棧健壯但低功耗計算機視覺分析的圖像信息數字化儀表和繼電器。現在Okinawa-based公司約有3500名活躍相機在全球500個地區,和提高了5.9億日元(約410萬美元今天)下一階段的業務。標準件投資者包括:JIC風險增長投資,三菱UFJ首都東京世紀維基金,衝繩開發金融公司,衝繩的科技發展中心,多根β。B輪,其2021年220萬美元的兩倍。 The company has received FCC and ISED certification for its devices and is preparing to launch in the U.S. and Canada. They plan to double their camera deployments and then rapidly expand afterwards. A Lilz device in a real world situation, and an example of its readouts. (Not the same gauges, to be clear.) As far as the hardware, Lilz has been working on getting “intrinsically safe” certification as well, meaning the cameras pose no risk of creating safety issues, for example shorting out and causing a spark that could ignite inflammable fumes. This frequently involves large enclosures for devices, but Lilz designed for it from the start, and its intrinsically safe cameras will only weigh 550 grams. They’re also planning on releasing a thermal camera with similar qualities to the RGB one; thermal monitoring is important in uncrewed power stations, where a person would simply have to visit with a handheld thermal camera to check. Naturally automating this process is desirable. Like other widely distributed businesses like gas storage and delivery, removing the need for these checks is not only safer, but saves money, time, and fuel. Although it would be a stretch to call Lilz an AI company, it’s certainly close enough to claim kinship while the AI market continues to expand. Though it regularly improves its computer vision algorithms and the methods of accessing the data, Kuba Kolodziejczyk, the company’s CTO, said they’ve seen interest beyond meter-reading, since the devices are often at key locations in facilities. “While we focus on analog gauges, with our cameras clients can also capture other aspects of their processes they couldn’t track before, and are asking us for capabilities to detect events of interest,” he told TechCrunch. “Some examples we see now are abnormal temperature changes (which ties back to our thermal vision camera offering) and leaks, for both equipment and surrounding environment.” Lilz devices could learn to detect outliers with very sparse data, he said, but cautioned that “this project is still in exploration phase.”