一种机器学习的人工智能系统，旨在在建筑工地上标记安全危害，再次为法官提供了支持ENR’s annual photo contest. Known as “VINNIE”— Very Intelligent Neural Network for Insight and Evaluation—the software uses object recognition technologies similar to those in an autonomous vehicle to analyze construction photos and videos for risks. Developed two years ago by Cambridge, Mass.-based Smartvid.io Inc., the system matches pixels in images to a library of objects to automatically tag or note the absence of specific items, such as hardhats, gloves or safety colors.
在2016年，EN新利luckR和几家行业公司贡献了数千个施工图像，以帮助培训和测试Vinnie。该系统从Enr的Photo-Contest数据库中处理了未识别的图像，以帮助启动软件。新利luck该产品的基本危险智能智能水平也是在2017年作为免费的公共事业引入的。
自从ENR在2016年的建筑摄影大赛中部署以来，Vinnie的准确性和能力已经提高。新利luck除了扫描硬汉和安全颜色外，Vinnie现在还可以看到手套和眼镜。在观看了参加今年比赛的763张图像之后，Vinnie发现了97人不戴手套，31人没有硬汉，89人没有安全颜色，11人没有眼镜。在每种情况下，人类专家都可以决定这些实例是否描述了可行的风险。
Vinnie标记了Enr的人类法官选择的两张照片。新利luck一个人是一个无手的工人，其手被部分遮盖。另一个显示了两名没有高可见性背心的铁工。ENR decided to publish both photos after conferring with this year’s contest safety judge, Keith Snead, safety director at Limback Holdings Inc. Snead says that while the workers “may be violating site-specific requirements set by general contractors,” they aren’t violating Occupational Safety Health Administration regulations.
Smartvid.io的创始人兼首席执行官Josh Kanner说，发现手套是“重要的补充”，因为他的几个客户“由于手工撕裂的高度和成本，他采用了100％的手套合规性政策。”根据美国劳工统计局的说法，手部受伤是涉及私营企业工作日期的主要非致命伤害之一。
Boston-based contactor Suffolk—which uses Smartvid.io on many of its projects—began requiring gloves about 18 months ago. Marty Leik, Suffolk’s regional safety manager, says VINNIE has helped improve personal protective equipment (PPE) compliance rates among subcontractors. Leik, who helped judge ENR’s 2016 photo contest, uses VINNIE to identify specific jobsite areas and any trades that are not 100% PPE compliant. “That allows us to engage that trade partner and follow up with them to implement improvements,” says Leik, who stressed that VINNIE isn’t used to punish individuals but is used “strictly for improvement and the benefit of everyone on the site.”
Leik想维尼recognize harnesses and tethers as well as fall exposures such as open holes or missing guardrails, items Kanner says are more challenging to detect. “You need to know if there’s an edge before you alert that there’s a missing guardrail, versus this is just two columns that have nothing in between them,” Kanner says. “Things like a span between two columns missing a guardrail requires a lot of context.”
Kanner says VINNIE will be able to recognize slip, trip and fall hazards such as debris and disorderly piles of materials by the end of Q1.
But because the definition of a “messy jobsite” is “ambiguous,” Kanner says VINNIE won’t just flag an area for merely having a certain number of errant coffee mugs on the ground; rather VINNIE is learning to “look at everything in an image and decide for itself” if the area poses a threat, Kanner says.
Smartvid.io has also integrated with several other systems during 2017, such as Autodesk’s BIM 360 Field. An integration with OxBlue’s construction time-lapse cameras recently went live and will be formally announced later in Q1. “The integration takes less than 90 seconds for the user to set up,” Kanner says, “and then data starts flowing from one or many OxBlue cameras on your site into the Smartvid.io platform.”
公司开始使用维尼超过汁液t safety. Clayco Inc. is streamlining progress tracking by comparing images uploaded to Smartvid.io with actuals on jobsites. Voice tags in the field help to automatically align content in the Smartvid.io app with specific keywords for machine learning for voice analytics.
Clayco also is cataloging years of imaging data based on content categories such as “tilt-up construction” so it can easily be recalled for marketing and other purposes, “as opposed to having this content idly laying on servers and hope that somebody one day can find it,” says Tomislav Žigo, Clayco’s vice president for virtual design and construction.
Žigo ultimately imagines using VINNIE to recognize building components such as concrete and rebar and to optimize site logistics by analyzing potential site hazards and egress routes. Perhaps VINNIE could even flag a worker for using a tool in a manner that could cause an injury.
Žigo说：“任何可以自动识别和标记的东西，我们发现有用。”
