The Reality Editor, a tool developed by the Fluid Interfaces Group at Massachusetts Institute of Technology, points to a future in which everything from chairs and beds to televisions and cars can be connected, manipulated and controlled in new ways. 麻省理工学院(MIT)“流体界面小组”(Fluid Interfaces Group)研发的工具“现实编辑器”(Reality Editor)给我们展出了这样的未来：从椅子、床到电视、汽车的一切物品都需要以新的方式相连、操控和掌控。Household objects equipped with processors and communications capabilities can, for example, be programmed so that your bed can turn on the heating system in your car as soon as you get up in the morning. 比如，可以对配有处理器和通信功能的家用物品展开编程，这样你早上一起来，你的床就不会启动你的汽车的供暖系统。But if such technologies might make home living more convenient, they will also usher in profound changes for businesses and society. 但是，如果说这些技术可能会让家居生活更加便捷，那么它们也不会给企业和社会带给种种深刻印象变化。
Critically, internet of things technologies — which include processors, software and web-enabled sensors — also allow objects to capture and transmit data instantly and constantly. 最重要的是，包括处理器、软件和可联网传感器在内的物联网技术，让物品需要连续不断地瞬间捕捉到数据并展开传输。On the plus side, this can pave the way for the delivery of more efficient services. In New York, for example, rubbish bins and recycling units developed by Bigbelly, a US-based technology and waste management company, can automatically notify collection agencies when they are full. 好的一面是，这为获取更高效率的服务铺平了道路。
比如，在纽约，美国科技和废品处置公司Bigbell研发的垃圾箱和回收站需要在剩了以后自动通报搜集机构。With everything from lampposts and traffic lights to weather satellites generating information all the time, cities can now analyse data to improve the world around us. Harriet Green, general manager of internet of things and education for US technology company IBM, says: “Knowing from these predictive models where the pollution is coming from allows city planners to make important decisions on how to improve air quality.” 鉴于从灯柱、交通灯到气象卫星的一切每时每刻都在产生信息，如今的城市可以对数据展开分析以提高我们的生活环境。美国科技公司IBM物联网和教育总经理哈丽雅特格林(Harriet Green)回应：“通过预测模型获知哪里在产生污染，需要让城市规划者就如何提高空气质量作出最重要决策。
” Such technologies offer companies the chance to cut costs, says Gabe Batstone, chief executive of Contextere, a software start-up that develops services for industrial workforces based on machine learning — the technique behind much artificial intelligence — and internet of things technologies. With sensors generating data on the status of equipment, the work of maintaining machinery and preventing breakdowns will be transformed, saving companies large amounts of money, Mr Batstone says. 软件初创企业Contextere首席执行官盖布巴特斯合(Gabe Batstone)回应，这些技术给企业获取了缩减成本的机会。该公司基于机器学习（很多人工智能背后的技术）和物联网技术开发面向工人的服务。
巴特斯合说道，传感器产生有关设备状态的数据，使机器确保和故障避免工作完全好转，为企业节省大量资金。“There’s information on the device, the device knows what maintenance is needed and the employee has access to a supercomputer — otherwise known as a cell phone — right there,” he says. “That’s going to have a monumental impact on business operations.” “设备上有信息，设备告诉必须何种确保，雇员可以通过一台超级计算机——或者叫做手机——获知信息，”他说道，“这将给商业运营带给深远影响。” In the water industry, for example, sensors can supply continuous data on the physical integrity of pipes, helping to detect weaknesses and prevent leaks. 比如，在水务行业，传感器可以连续不断地获取有关管道完好性的数据，协助观测脆弱之处，避免外泄。The same principle can also be put to work in the human body. Wearable and implantable sensors that can track everything from blood sugar levels to heart rates will allow irregular or life-threatening symptoms to be detected early. They will also enable people to take steps — through changes to diet or exercise regimes — to manage conditions such as diabetes or to lower their risk of illness. 某种程度的原则也可应用于人体。
可穿着和可植入传感器需要跟踪从血糖水平到心率的一切体征，从而尽早检测出不规律或者威胁生命的症状。这些传感器还能让人采行转变饮食或磨练方式等措施，来应付糖尿病等病症或者减少患有疾病的风险。
This could turn healthcare from a system designed to cure diseases and repair injuries to one that works to prevent illness and maintain good health. 这有可能使医疗从一个目的化疗疾病，修缮痛苦的体系，转化成为目的防治疾病，维持身体健康的体系。Of course, such changes also have implications for human resources. When equipment can be fixed remotely and patients remain at home, engineers and nurses may need to take on different roles. For some companies, it will mean hiring people with new skills. 当然，这样的变化也不会对人力资源导致影响。当设备可以加装在距离很远的地方，病人可以待在家中时，工程师和护士也许必须分担有所不同的职责。
对一些企业而言，这将意味著雇用不具备新技能的人。The advent of smart thermostats such as Nest, for example, means plumbing and heating companies now need IT skills since a system breakdown may have as much to do with a broadband connection as with the pipes or the boiler. “It’s turned that industry on its head,” says Tim Devine, a digital business expert at PA Consulting Group. 比如，Nest等智能恒温器的问世，意味著管道和暖气公司现在必须IT技能，因为系统的故障有可能和管道或者锅炉有关，也有可能和宽带相连有关。
“这让这个行业再次发生了翻天覆地的变化，”博安咨询(PA Consulting)数字业务专家蒂姆迪瓦恩(Tim Devine)说道。“The guy running a boiler company, where the key still is engineering, pipes, gas and big chunks of metal, is now running an IT company.” “尽管一家锅炉公司的关键仍然是工程、管道、天然气和大型金属件，但运营锅炉公司的人现在运营着IT公司。” Internet of things technologies will also create a need for new services and business models. “It’s great that I can get a warning on my smartphone telling me someone is walking around my house,” says Mr Devine. “But I need to be able to ring a local security service, otherwise I’m just worried.” 物联网技术还不会促成对新的服务和商业模式的市场需求。
“我能从智能手机上接到警告，告诉他我有人在我家周围晃悠，这有趣，”迪瓦恩说道，“但我也必须需要约见当地的安保服务，否则我不能干着急。” Moreover, because these new models depend on a complex system of organisations — from software companies to broadband service providers and device manufacturers — questions of liability will arise. 此外，由于这些新模式各不相同从软件公司、宽带服务提供商到设备制造商等多个的组织构成的简单系统，将产生责任归属于的问题。Mr Devine cites the example of a home heating system: “What happens with the boiler if the thermostat turns itself up while you’re away and you come back to a ￡1,000 heating bill. Whose liability is that?” 迪瓦恩荐了一个家庭供暖系统的例子：“如果恒温器在你不出的时候把锅炉关上，你回去以后接到了1000英镑的供暖费账单。
谁来分担这个责任？” While such questions have yet to be addressed, Mr Batstone argues that consumer technology has already paved the way for adoption of the internet of things by a broad range of businesses. 尽管这样的问题仍未获得答案，但巴特斯合指出，消费者技术早已为物联网被各类企业使用铺平了道路。“In our personal life, we’re used to our calendar telling us what time to leave to go to a meeting, giving us a map and checking the traffic,” he says. “在我们的个人生活中，我们早已习惯由我们的日历告诉他我们什么时候该去参与会议、获取我们地图，并查阅交通状况，”他说道。“So what the consumer side has already done is to allow us to accept that artificial intelligence and machine learning can be useful.” “因此，消费末端早已让我们拒绝接受这样一点，那就是人工智能和机器学习有可能是简单的。
本文来源：新利体育官网-www.tyresquaremis.com
