奧斯丁是美國唯一的F1賽事冠軍賽大本營，在該城市美洲賽道的后勤維修站，F(xiàn)1賽事粉絲人頭攢動(dòng)。隨著陣風(fēng)劃過瀝青跑道，一些人握緊了雨披，面部緊繃。其他人則在為自己和賽車拍照，并希望見到自己最喜愛的車手。當(dāng)某位車手最終現(xiàn)身時(shí)，人群立刻涌上前去，向其索要簽名和合影，而賽車則暫時(shí)被拋之腦后。

然而，這些賽車每一輛都價(jià)值900多萬美元，僅方向盤的造價(jià)就達(dá)到了約7.7萬美元。這些造價(jià)高昂的精密設(shè)備不僅能夠以時(shí)速約320公里的速度在跑道上飛馳，同時(shí)也是智能設(shè)備。這得益于賽車所攜帶的數(shù)十個(gè)傳感器，每個(gè)傳感器都會(huì)與跑道、后勤維修人員、現(xiàn)場播報(bào)人員和位于歐洲本土的第二工程師團(tuán)隊(duì)進(jìn)行通訊。

The Pit Row at the Circuit of the Americas in Austin, home to the only Formula 1 championship race in the U.S., is packed with fans. Some people clutch their ponchos and wince as gusts whip along the asphalt. Others snap photos of themselves with the cars and hope for a glimpse of their favorite driver. When one finally makes an appearance, a scrum surrounds him, asking for autographs and selfies. The vehicles are momentarily forgotten.

But these machines, each valued at more than $9 million (a steering wheel alone is worth $77,000 or so) are more than just pricey contraptions capable of whizzing around the track at more than 200 miles per hour. They are also intelligent, thanks to the many dozens of sensors fastened to them. Each sensor communicates with the track, the crew in the pit, a broadcast crew on-site, and a second team of engineers back home in Europe.

大部分F1觀眾認(rèn)為，賽事的勝負(fù)取決于賽車在大獎(jiǎng)賽賽道中坡道和急轉(zhuǎn)彎道的表現(xiàn)，但很少有人會(huì)意識(shí)到，這一賽事還是全球高性能互聯(lián)計(jì)算機(jī)之間的角逐。

F1賽事是一個(gè)所謂的高風(fēng)險(xiǎn)物聯(lián)網(wǎng)案例，在賽事期間，各個(gè)團(tuán)隊(duì)都利用了從實(shí)體目標(biāo)中獲取的大量實(shí)時(shí)數(shù)據(jù)。體育賽事對這類數(shù)據(jù)的使用方法尤為先進(jìn)，甚至一些團(tuán)隊(duì)還向其他行業(yè)輸出這類專長，在這些行業(yè)中，瞬息之間完成的海量信息分析往往關(guān)乎他人的性命。例如，英國汽車生產(chǎn)商邁凱倫正在向康菲分享其數(shù)據(jù)系統(tǒng)專長，以便后者將其運(yùn)用到自身油井設(shè)備當(dāng)中。

“在比賽中，我們會(huì)測量需要管理的一切事物，然后進(jìn)行建模，從而對賽車今后的表現(xiàn)進(jìn)行智能預(yù)測。”邁凱倫應(yīng)用技術(shù)首席創(chuàng)新官杰夫?麥格拉斯說。

邁凱倫團(tuán)隊(duì)以歷史數(shù)據(jù)和實(shí)況模擬（利用當(dāng)前賽季傳感器獲取的數(shù)據(jù)）為依托，并按照各條跑道的特性來制造賽車。公司利用3D打印機(jī)來制作原型部件，然后在風(fēng)洞中加以測試。通過測試的車身設(shè)計(jì)將用碳纖維進(jìn)行構(gòu)造。這一流程確保了汽車設(shè)計(jì)的每一個(gè)環(huán)節(jié)都能夠用數(shù)據(jù)來說話。

傳感器安裝在賽車的底盤和輪胎中以及引擎的各個(gè)部位。它們將測量空氣對車頭的壓力和下向力、剎車溫度、輪胎壓力，甚至賽車在彎道時(shí)是在滑動(dòng)還是主動(dòng)轉(zhuǎn)向。安裝在懸掛系統(tǒng)的傳感器測量的是賽車的速度以及受力對賽車的影響。那價(jià)值7.7萬美元的方向盤呢？它裝有能夠完成所有動(dòng)作的旋鈕、按鍵和踏板，車手只需通過按鍵便能完成從減速一直到向車手頭盔中注射液體的動(dòng)作。

然而，車手對賽車傳感器提供的數(shù)據(jù)卻是知之甚少。英菲尼迪紅牛車隊(duì)技術(shù)合作方負(fù)責(zé)人阿蘭?匹斯蘭德說：“我們盡量不拿數(shù)據(jù)去干擾車手，車手在駕車時(shí)會(huì)將自己的感知能力提升到極限。”

F1賽事對于獲準(zhǔn)進(jìn)入跑道的團(tuán)隊(duì)人員數(shù)量有著嚴(yán)格的規(guī)定。例如，英菲尼迪紅牛車隊(duì)在賽事現(xiàn)場擁有60名工程師，還有30名在英格蘭。匹斯蘭德表示，將數(shù)據(jù)從距離最遠(yuǎn)的澳大利亞跑道傳至車隊(duì)英國團(tuán)隊(duì)所需的時(shí)間不到300毫秒。該團(tuán)隊(duì)將藉此進(jìn)行實(shí)況模擬，以確定競賽各個(gè)環(huán)節(jié)的策略，包括換胎時(shí)間以及超車的時(shí)機(jī)。他說：“車手基本上不會(huì)再靠直覺來做決定。”

然而，數(shù)據(jù)分析并沒有解決所有的問題。目前，人們?nèi)詿o法精確地感知車身外側(cè)是否在跑道上，也無法確定輪胎對路面的抓地能力。只有車手才能回答上述問題。麥格拉斯說：“車手仍是我們所能擁有的最好的傳感器。”（財(cái)富中文網(wǎng)）

譯者：馮豐

校對：詹妮

Most Formula 1 spectators expect the race to be won or lost in the hills and hairpins of a Grand Prix circuit. What few realize is that it’s also playing out in powerful, interconnected computers around the world.

A Formula 1 race is a high-stakes example of the so-called Internet of things, where teams tap tremendous amounts of real-time data culled from physical objects. The sport’s use of such information is so sophisticated that some teams are exporting their knowledge to other industries where analyzing enormous amounts of information in the blink of an eye can mean the difference between life and death. For example, British automaker McLaren is sharing its data systems expertise with ConocoPhillips for use on oil rigs.

“We measure whatever we need to manage during the race, and then we model to get the predictive intelligence on how the cars are going to perform,” says Geoff McGrath, chief innovation officer at McLaren Applied Technologies.

The McLaren team builds its race cars for each track based on historical data and simulations generated by the current season’s sensor data. It builds prototype parts with 3D printers and tests them in wind tunnels. Approved designs are constructed in carbon fiber. The process ensures that every aspect of the car’s design is based on data.

Sensors are installed along a car’s chassis, in its tires, and throughout the engine. They measure the stress and downward force of the air on the car’s nose, brake temperature, tire pressure, and even whether the car is sliding or actively turning a corner. Sensors attached to the suspension measure the car’s speed as well as how force affects the vehicle. And that $77,000 steering wheel? It’s packed with knobs, buttons, and pedals that can do everything from slow down the car to deliver a shot of liquid to the driver through his helmet at the press of a button.

Yet for all the data generated by the car, the driver sees little of it. “We keep it to a minimum,” says Alan Peasland, head of technical partnerships at Infiniti Red Bull Racing. “They are maxed out on their cognitive capacity driving these cars.”

Formula 1 has strict rules about the number of team personnel allowed at the track. Infiniti Red Bull, for example, has 60 engineers on-site and 30 in England. It takes less than 300 milliseconds for the data from the farthest track in Australia to reach Infiniti Red Bull’s U.K. team, Peasland says, which runs simulations to determine race strategy for everything from a tire change to an attempt to overtake another driver. “Gut-feel decisions just aren’t made,” he says.

Data analytics haven’t solved everything. There’s still no way to get an accurate sense of where the cars are laterally on the track, and it’s impossible to determine how well a tire is gripping the roadway. The only person who can tell that is the driver. Says McGrath: “The driver is still the best sensor we have.”