:00:00. > :00:07.Comey into his links with Russia. That is your lot from me but now on
:00:08. > :00:11.BBC News week. -- week. This week, swaying
:00:12. > :00:18.votes on Facebook. And the stretchy and slimy world of
:00:19. > :00:54.soft robotics. It is hard to believe that the world
:00:55. > :00:59.is safer than it used to be. It is but the nature of terror attacks in
:01:00. > :01:02.the west in the last few years, the increasing use of vehicles, knives
:01:03. > :01:06.and guns to carry out prolonged attacks have forced authorities to
:01:07. > :01:17.think differently about how to deal with a terrorist incident. And, of
:01:18. > :01:21.course, they are not confined to the west. In some parts of the world
:01:22. > :01:28.these atrocities are more common and often have more casualties. It is
:01:29. > :01:31.difficult to predict when and where a terrorist attack will occur but
:01:32. > :01:39.while the authorities cannot predict, they can prepare for the
:01:40. > :01:46.worst. This is a large-scale counterterrorism training exercise.
:01:47. > :01:49.It was a combined effort, including London's Metropolitan Police, fire,
:01:50. > :01:53.ambulance and river services. However, training on this scale is
:01:54. > :01:57.expensive and requires large numbers of personnel and huge amount of
:01:58. > :02:02.planning, so it can't happen that often. But there are new ways to
:02:03. > :02:07.train more people individually. Mark Chisholm ACAS been taking part in a
:02:08. > :02:14.new type of terror training. -- has been taking part. Since 2015 from
:02:15. > :02:17.all across Europe a group of 14 partners including law enforcement,
:02:18. > :02:21.emergency services, transport companies and universities have been
:02:22. > :02:24.working together on a three-year project to create training
:02:25. > :02:29.simulation for real-world terrorist attacks.
:02:30. > :02:32.The project is called Auggmed and has been funded by an EU
:02:33. > :02:37.Part of it has been designed here at Sheffield Hallam University.
:02:38. > :02:39.Rather than build new technologies from the ground up, the hardware
:02:40. > :02:43.and software that is at the core of this training system is tech
:02:44. > :02:45.that is more commonly found in video games.
:02:46. > :02:50.And that technology is proving to be a flexible training tool.
:02:51. > :02:54.You can act out a lot more scenarios that would be too dangerous to do
:02:55. > :03:04.It's a lot cheaper, it's more cost effective,
:03:05. > :03:06.it's easier to set up, and it offers a whole
:03:07. > :03:09.range of scenarios that you couldn't do in real life,
:03:10. > :03:12.because they would just be too dangerous or too complicated.
:03:13. > :03:16.Virtual simulations that can be used to train a wide variety
:03:17. > :03:18.of different people, from paramedics to the police,
:03:19. > :03:20.and even those employed by the transport networks.
:03:21. > :03:24.For this scenario we're going to put a new bag down here.
:03:25. > :03:29.And so the trainees are going to be looking for this bag.
:03:30. > :03:32.A suspect bag has been placed in an accurate virtual model
:03:33. > :03:34.of a real location - a subway station in the Spanish
:03:35. > :04:01.There is what I'm assuming is some kind of explosive
:04:02. > :04:06.So in this situation I'm going to start evacuating
:04:07. > :04:17.I'm going to tell them to start to evacuate.
:04:18. > :04:21.Now your people are evacuating towards the bomb,
:04:22. > :04:25.So you might want to go on the platforms to start evacuating
:04:26. > :04:30.So all of the passengers are all being driven by an AI, yeah?
:04:31. > :04:33.But the people behave in a pretty realistic fashion?
:04:34. > :04:37.That's all based on scientific data of what people do
:04:38. > :04:41.So you've successfully started evacuating everybody who has been
:04:42. > :04:51.We can't show too much of this as the images are just too graphic.
:04:52. > :04:54.In the aftermath of an explosion, a paramedic trainee must triage
:04:55. > :04:56.the injured passengers, applying different coloured
:04:57. > :05:01.The different colours indicate the urgency
:05:02. > :05:07.It's an unsettling and distressing experience.
:05:08. > :05:14.Overwhelming sound and distressing images are designed to replicate
:05:15. > :05:20.But this system isn't just the work of counterterrorism researchers
:05:21. > :05:27.To find out more, I travelled to the real location
:05:28. > :05:39.In recent years, terrorist atrocities have been carried
:05:40. > :05:41.out all over Europe, highlighting the international
:05:42. > :05:43.nature of the response to this terrorism.
:05:44. > :05:45.Here in Barcelona, the emergency services themselves have played
:05:46. > :05:48.a key role in the design of the Auggmed virtual
:05:49. > :05:55.Jose Jurado is a doctor and emergency first
:05:56. > :06:04.He's been helping to fine tune the system to improve
:06:05. > :06:05.its utility to emergency services and paramedics.
:06:06. > :06:09.So this is the station that I saw in the VR model?
:06:10. > :06:12.What is the big thing that you get from the virtual
:06:13. > :06:15.reality, from the fact that it is so immersive, that
:06:16. > :06:22.When I get to a real situation, I am used to it,
:06:23. > :06:29.So it doesn't surprise me so much as it could.
:06:30. > :06:31.It is quite unusual being in the real station,
:06:32. > :06:39.having spent a little bit of time in the virtual version.
:06:40. > :06:42.What has been interesting walking around here is noticing
:06:43. > :06:45.I now know the layout, the geography of the station.
:06:46. > :06:48.I know where all of the exits are, I know where the escalators are,
:06:49. > :06:52.and which direction of travel they go in.
:06:53. > :06:55.So even I was able to learn something very, very quickly in that
:06:56. > :06:57.virtual reality version of this subway station.
:06:58. > :07:01.Robert Guest is from Birmingham University and is part
:07:02. > :07:12.You can't really get a physical hands on an object in virtual
:07:13. > :07:14.reality, but what we can trade is things like
:07:15. > :07:18.We can look at emotional management and general communication skills
:07:19. > :07:23.We see terrorists constantly changing their tactics.
:07:24. > :07:29.How do you guys respond to those changes of tactics?
:07:30. > :07:32.The benefit of this project as a whole is we can rapidly
:07:33. > :07:40.change what scenarios are actually being trained.
:07:41. > :07:43.So for new tactics being used, out in the public, in reality,
:07:44. > :07:47.we can bring those into a virtual world and allow people to train
:07:48. > :07:51.The next stage of this system's development is a haptic vest,
:07:52. > :07:53.which provides force feedback to trainees simulating
:07:54. > :07:58.It's also fitted with heating elements, which make
:07:59. > :08:05.If you are in a stressful environment like this one,
:08:06. > :08:07.there is a good chance you will start to get
:08:08. > :08:14.As soon as you get uncomfortable, then that makes it a lot more
:08:15. > :08:17.difficult to do your job and creates an environment for them
:08:18. > :08:21.which is as close as it can be to the real one.
:08:22. > :08:23.This whole system isn't designed to replace real-world
:08:24. > :08:26.training but to augment it, to allow people to betray
:08:27. > :08:28.dramatically if need be, constantly reinforcing their skills.
:08:29. > :08:31.Skills which recently have been sadly tested all too often.
:08:32. > :08:37.Now, while the professional first responder is always
:08:38. > :08:40.going to be better trained, it is ask the public who are almost
:08:41. > :08:45.always going to be first on the scene of an attack.
:08:46. > :08:48.Current advice from the British police is to run from an incident,
:08:49. > :08:55.rather than surrender or try to negotiate with attackers.
:08:56. > :08:58.This online video also explains how and where to hide
:08:59. > :09:10.Now, if you dial 999, but it is not safe to talk out loud,
:09:11. > :09:13.the operator will give you the option to dial 55,
:09:14. > :09:16.to show you haven't called by accident and you really
:09:17. > :09:19.55 looks like SS, which stands for silent solution.
:09:20. > :09:22.There is also an app called Citizen Aid, which uses advice
:09:23. > :09:25.from combat situations to help users administer first aid and make more
:09:26. > :09:41.informed decisions in different emergency situations.
:09:42. > :09:44.Hello and welcome to the week in tech.
:09:45. > :09:47.It was the week that Uber refunded customers for journeys taken
:09:48. > :09:50.near last Saturday night's London terror attacks, after pricing had
:09:51. > :09:52.automatically surged due to demand - a function they disabled
:09:53. > :10:00.The comment section on Britney Spears Instagram account
:10:01. > :10:05.has been used by Russian speaking hackers to test malware.
:10:06. > :10:09.And Snapchat specs have gone on sale in the UK.
:10:10. > :10:12.If you think this is a sensible way to go out.
:10:13. > :10:14.Google's Streetview cars have been tracking air pollution.
:10:15. > :10:18.After a year of the vehicles driving around the streets of Oakland,
:10:19. > :10:20.California, data localised to individual roads has become
:10:21. > :10:22.available, with initial recordings of black carbon,
:10:23. > :10:24.nitric oxide and nitrogen dioxide being revealed.
:10:25. > :10:27.Anyone with kids can tell you what it's like trying to get
:10:28. > :10:41.But, sadly, I don't have a new gadget to tell you about that.
:10:42. > :10:44.It's actually the play clay that's gone high-tech.
:10:45. > :10:46.Doh Universe can conduct electricity and aims to help kids
:10:47. > :10:48.learn about circuits, sound, light and
:10:49. > :10:51.And, finally, researchers at MIT have developed sensors
:10:52. > :10:55.for the grippers of robotic arms that aimed to help bots grab things
:10:56. > :10:58.with the right amount of pressure. The GelSight sensors aim to make
:10:59. > :11:00.negotiating smaller objects possible, as well as making general
:11:01. > :11:03.household tasks easier to approach - which would be handy,
:11:04. > :11:21.if one day robots are to become ordinary household companions.
:11:22. > :11:24.This annual running of the nerds can only mean one thing.
:11:25. > :11:26.We are in San Jose for Apple's worldwide developers' conference,
:11:27. > :11:31.It's an event the company doesn't typically used to make big
:11:32. > :11:33.product announcements, but, this year, perhaps
:11:34. > :11:35.feeling the heat a little, they broke with tradition
:11:36. > :11:44.It's been 15 years since we held the developer conference in San Jose
:11:45. > :11:56.The HomePod is a direct competitor to assistance made
:11:57. > :12:00.It will cost $349 and be available later this year
:12:01. > :12:10.It will be controlled by Siri, but Apple isn't really calling
:12:11. > :12:19.They say it is a music device first and foremost.
:12:20. > :12:22.We weren't allowed to film it in action, but I was given
:12:23. > :12:24.a private listen and, well, it does sound fantastic.
:12:25. > :12:28.One of the potential downside is that you need an Apple music
:12:29. > :12:30.subscription in order to get the full integration.
:12:31. > :12:33.So if you prefer to use Spotify or Pandora, maybe not
:12:34. > :12:37.In other news, Apple says it can become the biggest augmented
:12:38. > :12:41.This demo is from the new production house run by Peter Jackson,
:12:42. > :12:45.the man famed for creating the Lord Of The Rings movies.
:12:46. > :12:48.And the iPad has been given a new lease of life.
:12:49. > :12:52.They announced a new 10.5 inch iPad pro and the next version of Apple's
:12:53. > :12:57.operating system will see the tablet get a bunch of extra features.
:12:58. > :13:01.Many people might see this as a kind of middle ground between getting
:13:02. > :13:03.a very expensive computer, but still being able
:13:04. > :13:13.Several thousand developers turn up to WWDC every year.
:13:14. > :13:15.Many more would come if they could get tickets.
:13:16. > :13:17.Among the masses, I found the youngest attendee,
:13:18. > :13:20.a ten-year-old who had come all the way from
:13:21. > :13:29.I just enjoy the fact that I can turn, like,
:13:30. > :13:31.my ideas into reality by programming and making apps.
:13:32. > :13:35.So this is my most recent app, which I published six days ago.
:13:36. > :13:37.You can click anywhere to place a block.
:13:38. > :13:39.Your goal is to get the highest tower blocks.
:13:40. > :13:42.So you are obviously much younger than everybody here?
:13:43. > :13:45.So what do you want to do when you grow up?
:13:46. > :13:48.Are you going to carry on making apps?
:13:49. > :14:00.How can I just turn myself into a turtle and grow a shell?
:14:01. > :14:13.I would like to create apps I can revolutionise the world.
:14:14. > :14:17.And I also want to teach the world coding and get them into coding,
:14:18. > :14:20.so they can actually improve all the technology we have and make
:14:21. > :14:31.A young man destined for great things, I'm sure.
:14:32. > :14:35.Think robots and maybe you'll picture something like this.
:14:36. > :14:41.But what about robotic muscle and smart materials that
:14:42. > :14:46.could act as human skin, all clothes that rehabilitate
:14:47. > :14:55.Well, that is part of what's called soft robotics and this team
:14:56. > :14:57.at Bristol Robotics Lab are bioengineering technologies
:14:58. > :15:06.This is a bucket of alien saliva, right?
:15:07. > :15:09.Yeah, this is the same stuff that drips out of the alien mouth.
:15:10. > :15:13.So Ridley Scott just used a whole bunch of that.
:15:14. > :15:18.Though, in this case, it is to simulate blood.
:15:19. > :15:22.This soft robot mimics how some bacteria move through our bodies.
:15:23. > :15:26.In the future, it is thought that nano robots will take a similar trip
:15:27. > :15:30.through our veins looking for infection and illness.
:15:31. > :15:36.Some of the projects they are working on here involves
:15:37. > :15:40.making assistive technology for elderly and disabled people,
:15:41. > :15:43.like this pneumatic artificial muscle.
:15:44. > :15:47.It can be made into any shape and built into clothing.
:15:48. > :15:51.As you apply air, it changes its shape so it
:15:52. > :15:56.could for instance help people with limited grip strength.
:15:57. > :15:59.Its force is only dependent on how much air pressure you apply.
:16:00. > :16:02.And here is some material that can sense when that
:16:03. > :16:08.This diametric elastomer can detect when it's being stretched,
:16:09. > :16:12.so it can sense when you are trying to move and add extra power to maybe
:16:13. > :16:20.And it can not only detect movement, it can also change its shape
:16:21. > :16:22.when you apply a high enough voltage.
:16:23. > :16:25.You could use it for changeable clothing, clothing that
:16:26. > :16:29.You can use it as a sort of second skin to help
:16:30. > :16:32.with deep vein thrombosis, to assist with pumping blood.
:16:33. > :16:34.It can even be layered up to create stronger artificial muscles.
:16:35. > :16:38.It doesn't seem like it is doing a lot, but, actually,
:16:39. > :16:41.it is very thin, it weighs almost nothing - the active part
:16:42. > :16:43.of which only weighs, let's say, four grams,
:16:44. > :16:48.is complicated, none of this is extremely high-tech,
:16:49. > :16:51.using like billions of transistors, and it is simple voltage
:16:52. > :16:57.I think that is one of the big advantages of soft robotics,
:16:58. > :17:01.In a complicated robotic system you have a lot
:17:02. > :17:06.With these sorts of things it is very simple and
:17:07. > :17:09.The intelligence is in the design and immediately used,
:17:10. > :17:17.The robotics lab in Bristol is 50,000 square feet of innovation
:17:18. > :17:22.filled with hundreds of different types of robots.
:17:23. > :17:27.But what nearly all have in common is they need power to run.
:17:28. > :17:31.Over in the bio energy lab, scientists are working on one freely
:17:32. > :17:35.available resource the world will never run out of -
:17:36. > :17:41.Each one of these cylinders is a microbial fuel cell device.
:17:42. > :17:45.It turns waste water into electricity using microbes.
:17:46. > :17:52.That is their favourite item on the menu.
:17:53. > :18:00.In this unit, two litres of urine is fed into the fuel cell pack.
:18:01. > :18:04.The microbes eat what they need, creating electrons as a by-product.
:18:05. > :18:07.And because they are attached to an electrode's surface,
:18:08. > :18:11.it is all collected to produce about 30-40 milliwatts of power.
:18:12. > :18:14.Now that's enough to slowly charge a smartphone,
:18:15. > :18:18.power smart displays, or power internal lights
:18:19. > :18:26.When we do it out of the lab, we install these units out
:18:27. > :18:28.of the lab, we have many more of them connected
:18:29. > :18:36.If you are going to Glastonbury this year, you might see these
:18:37. > :18:42.If you choose to use the urinals, you'll be part of an experiment
:18:43. > :18:49.which is literally putting the P into power.
:18:50. > :18:54.These are E Ink displays, which don't require a lot of power.
:18:55. > :18:58.But a lucky few may be able to charge their phones for a bit,
:18:59. > :19:05.Most of the pee used here comes from staff donors at the lab.
:19:06. > :19:08.It's only good for the microbes for an hour or so,
:19:09. > :19:20.Around the world, scientists are looking at different ways
:19:21. > :19:24.Here, it is alternative sources of power.
:19:25. > :19:27.At soft robotics, it's smart materials and possibly
:19:28. > :19:32.But in Italy's Scuola Superiore Sant'Anna,
:19:33. > :19:41.Ana Matronic went there to look at attempts to simulate touch.
:19:42. > :19:44.I am at the biorobotics lab where researchers are trying
:19:45. > :19:47.to merge human physiology with machine engineering.
:19:48. > :19:50.The team are working on a bionic fingertip that is capable
:19:51. > :19:57.The human sense of touch is an incredibly complex one.
:19:58. > :20:01.I don't even need to look at these three pieces of plastic to sense
:20:02. > :20:04.the differences in the coarseness of the ridges.
:20:05. > :20:06.This of course presents a huge problem to people
:20:07. > :20:13.How do you transfer that same sensitivity into a prosthetic hand?
:20:14. > :20:18.To create a machine capable of sensing and transmitting tactile
:20:19. > :20:22.data, first we need to understand how bodies decode sensory stimuli.
:20:23. > :20:31.Fingertips have the highest concentration of sensation almost
:20:32. > :20:36.Thanks to 20,000 nerve fibres on each finger.
:20:37. > :20:42.They react to sensory information as we move our fingers
:20:43. > :20:50.Some respond to pain, some to temperature.
:20:51. > :20:55.Others react to pressure or vibration.
:20:56. > :20:59.This is the characteristic that allows our skin to interact
:21:00. > :21:02.with the environment and that will allow an object,
:21:03. > :21:08.The bionic fingertip registers the textures it touches
:21:09. > :21:14.On screen it may look simple, but that is exactly the language
:21:15. > :21:22.As we touch objects, it sends nerve impulses to the brain.
:21:23. > :21:26.And the tiny, subtle variations in how the skin deforms as we touch
:21:27. > :21:32.changes those impulses and how we perceive texture.
:21:33. > :21:36.This capitalises on an actual principle and can be more effective
:21:37. > :21:41.as humans and animals in general can interact with the environment.
:21:42. > :21:47.The professor and his team have already had some success.
:21:48. > :21:50.Dennis Sorensen was one of the first amputees to try out
:21:51. > :21:53.The output from the finger was directly connected
:21:54. > :21:57.to the healthy nerves in his upper arm.
:21:58. > :22:01.I could tell the difference between where it was very rough and smooth.
:22:02. > :22:11.And, since this first clinical trial a couple of years ago,
:22:12. > :22:14.the team had been trying to increase the number of textures
:22:15. > :22:21.The experiments that we are showing now are demonstrating
:22:22. > :22:25.the capability to encode, for examples silk, from cotton,
:22:26. > :22:31.from elastic, from wool, from different kinds of materials.
:22:32. > :22:34.And in this way we could restore a more natural sense
:22:35. > :22:41.of touch to the person wearing the prosthesis.
:22:42. > :22:44.What is learned here can be transferred to other applications.
:22:45. > :22:48.For example, a surgical robot could use this technology
:22:49. > :22:51.to identify tumours, which would feel different
:22:52. > :22:58.Another kind of application is for rescue.
:22:59. > :23:01.To allow to be present in the environment, not
:23:02. > :23:05.only through vision, but to have more senses available
:23:06. > :23:11.Think for example of the nuclear disasters, or in the case
:23:12. > :23:17.The robot can go and touch in the perceived environments,
:23:18. > :23:21.based also on the sensory feedback that you can have remotely
:23:22. > :23:30.it can be integrated into simple things like gloves.
:23:31. > :23:34.For instance, I could be anywhere in the world.
:23:35. > :23:38.My husband back in New York can give me the sensation of petting our cat.
:23:39. > :23:42.And that would be transferred through these actuators to me
:23:43. > :23:53.Well, I can't give you that at the moment, Ana,
:23:54. > :23:56.but in the meantime, how about a hug from this chap?
:23:57. > :23:58.That's it from the Bristol Robotics lab.
:23:59. > :24:02.Next week, we are going to be in Los Angeles for the annual E3
:24:03. > :24:09.We will tweet everything we see at BBC Click.
:24:10. > :24:12.You can also follow us on Facebook for loads of extra content
:24:13. > :24:36.Thanks for watching and we will see you in LA.
:24:37. > :24:40.It's felt a little more like autumn for some this week and although high
:24:41. > :24:43.pressure will build into next week and we'll hopefully see more
:24:44. > :24:48.of these skylines, this was sent in late in the day on Friday,