本集内容

Shark-detecting drones 可探测鲨鱼的无人机

学习要点

有关“Danger 危险”的词汇

边看边答

How does the drone know if it's spotted a swimmer or a shark?

文字稿

A shadow in the sea or something more sinister?

From the beach it's hard to tell but from the skies the drone has a clearer view. It feeds into deep learning software which it's claimed has a 92% success rate in spotting sharks, as well as less threatening species. Every time it sees a dolphin, whale or a swimmer in distress it learns their shape. Launched along the beaches of New South Wales the drones can patrol for 40 minutes. Daniel was one of the first to train as a lifesaver pilot. 

Daniel Trollope, Drone pilot

I mean, I can't physically run out and grab a board and paddle out and save someone, but sitting on the beach we’ve got eyes in the sky and we're just another layer of protection, really. 

The drones don’t only observe - they can react too, dropping an inflatable device to help people in the sea. It won't replace the use of controversial shark nets and drum lines however – which some claim do more harm than good. The drones won't be on every beach every day, but they should give everyone a better understanding of what’s down below. 

仅仅是一个影子？或是一个更危险的生物？ 

站在沙滩上看去，很难辨认出海上的阴影是不是鲨鱼，但空中无人机就能看到更清楚的图像。无人机将拍摄到的影像传输给分析海洋的智能软件，这个软件号称可以在探测包括鲨鱼和一些没那么危险的生物时达到92%的成功率。每当无人机看到遇险的海豚、鲸或游泳者时，便会记下一个新形状。在澳大利亚新南威尔士州的海滩沿岸上首次推出了利用无人机执行海上巡逻探测工作，每次探测时间达40分钟。丹尼尔是第一批接受操作无人机培训的“救生飞行员”。

丹尼尔·特罗洛普 无人机操作者

“虽然我不能亲自跑过去、拿上滑板，然后划过去救人，但我们坐在海滩上通过“天上的眼”可以一睹海里的情况，从而我们也就可以给大家提供多一层的安全保障。”  

无人机不仅能检测到海上的情况，还能做出及时的反应，比如扔下一个充气漂浮物来帮助在海上的人们。然而，它不能代替尚存争议的鲨鱼网和鼓线的使用，有些人认为使用鲨鱼网和鼓线的弊大于利。无人机上不会每天在每个海滩上巡逻，但它的使用应该能给人们提供一个更好地了解海底下情况的机会。

词汇

sinister
有凶兆的，危险的 

threatening
威胁（性）的，危险的

in distress
遇险

do more harm than good
弊大于利

你知道吗 ？

There are over 500 species of shark, ranging from the colossal 20m whale shark, which weighs around 30,000kg and is the world's biggest fish, to the tiny dwarf lantern shark that only grows to 10-20cm.

据统计，目前鲨鱼的种类超过500种，从体重约3万公斤的“世界上最大的鱼”— 鲸鲨，到长度只有10到20厘米的“鱼界的小矮人”灯笼鲨。

问题答案

It compares the shape against images and shapes stored in its deep learning software. It’s claimed to have a 92% success rate.