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We're live and standing by for your help to solve crime where you live. | :00:00. | :00:10. | |
Today, an overseas student working night shifts to make ends meet left | :00:11. | :00:12. | |
I really hope this guy gets caught soon, and maybe ever goes through | :00:13. | :00:29. | |
this again. And we are with West Midlands Police as they join forces | :00:30. | :00:33. | |
with East European office to combat cross-border crime. This vehicle has | :00:34. | :00:40. | |
no insurance, so this chap is committing an offence. | :00:41. | :00:43. | |
We're continuing our journey with the UK's police forces asking for | :00:44. | :01:00. | |
your help to hunt down the criminals who affect our everyday lives. | :01:01. | :01:03. | |
The mugger with a Friar Tuck haircut who struck seven victims. He was | :01:04. | :01:19. | |
choosing elderly ladies, easy pickings, I suppose. I just hope he | :01:20. | :01:26. | |
gets his comeuppance. And roadside rage as a man is | :01:27. | :01:29. | |
knocked to the ground by an angry driver, his worry is for the safety | :01:30. | :01:34. | |
of the female passenger. What has happened to me I have to deal with, | :01:35. | :01:38. | |
but she has to deal with that man's rage, and I hope that she can cope | :01:39. | :01:42. | |
with it, and if she can't, she should get in touch with somebody. | :01:43. | :01:45. | |
Today we're back in the West Midlands, and Sian and the team have | :01:46. | :01:48. | |
I may be in a secret location, but what I can tell you is that I'm | :01:49. | :01:55. | |
somewhere near Birmingham at the headquarters of the National | :01:56. | :01:57. | |
I'll be finding out how they trace a bullet back to | :01:58. | :02:00. | |
And we'll see the latest scanning kit | :02:01. | :02:04. | |
As you can see there's lots on solving gun crime today, and our | :02:05. | :02:11. | |
first appeal is to find the armed robber who confronted a student | :02:12. | :02:14. | |
I was just thinking about my mother at that second. I owe her a lot, and | :02:15. | :02:32. | |
I was thinking about her. The other thing I was thinking was, is this | :02:33. | :02:43. | |
it? Life over? Originally from Bangalore in India, he is now in his | :02:44. | :02:47. | |
third year studying aerospace engineering at Coventry University. | :02:48. | :02:52. | |
I always wanted to be a pilot. I always wanted to get into the | :02:53. | :03:08. | |
aerospace industry. Shashwath worked at a petrol station to fund his way | :03:09. | :03:12. | |
through university. It got me to interact with a lot of people, and | :03:13. | :03:17. | |
aid the bills. On the night of the 20th of April, around nine o'clock, | :03:18. | :03:21. | |
Shashwath found himself alone in the shop. It was a bank holiday Monday | :03:22. | :03:27. | |
the next day, so it is quiet. He had just sat down to text a friend when | :03:28. | :03:29. | |
he heard a noise. the next day, so it is quiet. He had | :03:30. | :03:32. | |
just sat down to text a friend I heard a click in the door, and I saw | :03:33. | :03:36. | |
it open, so I stood up. I couldn't see anybody, and I took a moment to | :03:37. | :03:41. | |
look down, and I saw some body crouched. The man put something in | :03:42. | :03:50. | |
the door to jam it open. I soon realised he had a mask on his face | :03:51. | :03:53. | |
and was covered with a hoodie, and he had a plastic bag in his hand. | :03:54. | :03:59. | |
CCTV shows the man standing up and making his way towards Shashwath at | :04:00. | :04:10. | |
the cash desk. He put the bag on the table, and said, put all of the | :04:11. | :04:16. | |
money in the bag. He had a gun. My eyes were on the trigger. I just | :04:17. | :04:20. | |
lifted my hands up, and I was thinking about my mum. He said, | :04:21. | :04:28. | |
nothing funny, nothing funny, put the money in the bag. He was waving | :04:29. | :04:33. | |
a gun, so I was really scared. I thought this was it, life is over. | :04:34. | :04:40. | |
Once the till was cleaned out, the gunman calmly turned and walked out. | :04:41. | :04:45. | |
He stopped at the door to remove the object he had used to prop it open. | :04:46. | :04:53. | |
Then I took a minute to sit down, and then I started breaking down and | :04:54. | :04:58. | |
breaking up. Though he made off with only a couple of hundred pounds, | :04:59. | :05:01. | |
police take armed robbery very seriously. By using a firearm, he | :05:02. | :05:08. | |
has put himself at considerable personal risk for not very much | :05:09. | :05:13. | |
money. This offence attract considerable sentence, and my team | :05:14. | :05:15. | |
are determined to put him behind bars. Since the robbery, Shashwath | :05:16. | :05:21. | |
has felt the separation from his mum in India more than ever. I used to | :05:22. | :05:26. | |
call her in the middle of the night to say hello, and she would ask if | :05:27. | :05:33. | |
everything is OK. My parents wanted to come here in the next month, and | :05:34. | :05:37. | |
I have had to tell them not to come, because I didn't want them to know | :05:38. | :05:40. | |
what is happening and what has been going on. I have just changed the | :05:41. | :05:45. | |
way I think, and I really hope this guy gets caught soon. I hope that | :05:46. | :05:54. | |
nobody ever goes through this again. Nick Dale, leading this | :05:55. | :05:58. | |
investigation, is with me now. He got away with only ?200. This is a | :05:59. | :06:09. | |
very serious offence, isn't it? That is right. By using a firearm, and he | :06:10. | :06:13. | |
has caused a lot of distress and risks a significant sentence. Is | :06:14. | :06:17. | |
this unusual for this part of commentary? -- Coventry? | :06:18. | :06:25. | |
Yes, very unusual to see a firearm used in this sort | :06:26. | :06:27. | |
It must have been extremely frightening. | :06:28. | :06:30. | |
A white man wearing a waist-length button jacket, a baseball cap | :06:31. | :06:34. | |
He's in his early 20s, of slim build with blue eyes and | :06:35. | :06:38. | |
He had a white gym glove and a JD sports bag that was ripped. | :06:39. | :06:47. | |
It was some sort of golf glove that he was wearing on his left hand. And | :06:48. | :06:54. | |
also a sports bag like this one, with a drawstring top. Those could | :06:55. | :07:02. | |
be vital in the attempted to get hold of this man. If you can help, | :07:03. | :07:04. | |
please get in touch. Now it's time to have a look | :07:05. | :07:08. | |
at today's Wanted Faces. First up today is this man, | :07:09. | :07:10. | |
64-year-old Allan Francis Goodin. He was jailed for three years | :07:11. | :07:13. | |
for 11 different offences including burglary, theft | :07:14. | :07:15. | |
and obtaining services dishonestly, He's failed to stick to | :07:16. | :07:17. | |
the conditions of his release Goodin is known to use at least 27 | :07:18. | :07:21. | |
different identities and has links 44-year-old Russell Broughton was | :07:22. | :07:26. | |
sentenced to four years in prison in April this year for his role | :07:27. | :07:34. | |
in a fight at a bar in Birmingham. Broughton failed to appear | :07:35. | :07:39. | |
in court for sentencing He was last known to be in the | :07:40. | :07:41. | |
West Midlands area. Next is this man, | :07:42. | :07:45. | |
Michael John Hayes. Detectives in Dorset want to | :07:46. | :07:49. | |
question him in connection with a distraction burglary in which | :07:50. | :07:51. | |
an elderly lady had items stolen. The 59-year-old has connections | :07:52. | :07:55. | |
to Brighton but where is he now? And last up today is | :07:56. | :08:00. | |
24-year-old Roger Balint. Detectives want to question him | :08:01. | :08:04. | |
in connection with an incident in April this year in which a car | :08:05. | :08:07. | |
was driven into a moped, causing Balint has links to the Greater | :08:08. | :08:10. | |
Manchester area and the Isle of Man. He also has a bald patch | :08:11. | :08:16. | |
on the top of his head. If you know where any of them are, | :08:17. | :08:20. | |
make sure you pick up the phone. Some network | :08:21. | :08:24. | |
and mobile operators will charge. Or text us on 63399, | :08:25. | :08:31. | |
and you'll be charged Or you can send us | :08:32. | :08:33. | |
an e-mail to [email protected]. In the last ten years, the number of | :08:34. | :08:39. | |
gun-related offences have halved, and that's partly due to the | :08:40. | :08:50. | |
establishment of NABIS, the National The state-of-the-art labs here have | :08:51. | :08:54. | |
the technology to pinpoint the exact gun used in a crime and whether it's | :08:55. | :08:57. | |
been involved in previous crimes. Martin Parker is head | :08:58. | :09:00. | |
of forensics here. I am comparing a test fired bullet | :09:01. | :09:11. | |
on the left to a bullet recovered from a crime scene on the right. Why | :09:12. | :09:18. | |
is that so important? In the UK, it is difficult for criminals to get | :09:19. | :09:21. | |
hold of guns, so they are used repeatedly. By doing these tests, we | :09:22. | :09:25. | |
can link between scenes when the same gun is used, and when a gun is | :09:26. | :09:29. | |
recovered, we can link it back to the previous scenes it has been used | :09:30. | :09:35. | |
in. You mentioned test-firing yesterday. We filmed you carrying | :09:36. | :09:39. | |
out some test-firing in the shooting range next door. It looked like you | :09:40. | :09:44. | |
were shooting into a block. Talkers through what you were doing. That | :09:45. | :09:51. | |
was ballistics. I was test-firing a self loading pistol. The bullet here | :09:52. | :09:57. | |
is the bullet from that weapon, and I am comparing it with one from a | :09:58. | :10:01. | |
previous crime scene. Normally I would be looking down the | :10:02. | :10:04. | |
microscope, but you can see what I can see down the microscope on the | :10:05. | :10:09. | |
screen there. So you are lining up the ridges? Yes, they are marks from | :10:10. | :10:20. | |
the barrel. Will that be left from a barrel on a particular bullet? These | :10:21. | :10:26. | |
marks are unique. You can see it is like a supermarket bar code. The | :10:27. | :10:30. | |
marks are unique to that barrel. So what I can say looking at this, | :10:31. | :10:35. | |
comparing these two bullets, I can say conclusively that they were | :10:36. | :10:38. | |
fired from the same gun. So the gun you saw testified yesterday is | :10:39. | :10:42. | |
definitely the gun which fired that crime scene bullet. Thank you for | :10:43. | :10:48. | |
taking us through that. The threat from guns is ever evolving, and this | :10:49. | :10:52. | |
scheme -- seems incredible. 3D printers can be bought | :10:53. | :11:03. | |
on the high street and they are able Dr Simon Leigh | :11:04. | :11:06. | |
from the university of Warwick has You can download this from the | :11:07. | :11:20. | |
Internet or draw it to the machine, it turned into software commands, | :11:21. | :11:24. | |
and draws it out and builds up your part in 3-D. So it is difficult for | :11:25. | :11:30. | |
normal manufacturer where it takes a block and shades it down, this build | :11:31. | :11:35. | |
it up. And how long does this process take? Anything from 20 | :11:36. | :11:40. | |
minutes to a number of hours, depending on the size of the parts. | :11:41. | :11:43. | |
Thank you for taking us through that. It will still be going | :11:44. | :11:47. | |
throughout the programme, and we're going to be coming back later in | :11:48. | :11:50. | |
that programme as well to check on this, so checking with us later on. | :11:51. | :12:08. | |
Now, we need your help to identify these criminals, and this is quite | :12:09. | :12:13. | |
upsetting. The robbers drag a staff member across the store, and one | :12:14. | :12:17. | |
pulls him into an aisle where he is beaten with a gun and punched | :12:18. | :12:22. | |
repeatedly. He is powerless to stop them grabbing cash from under the | :12:23. | :12:25. | |
till and emptying the cigarette display. They fill a bin liner with | :12:26. | :12:29. | |
tobacco is one of the men brandishes a black handgun. In just two | :12:30. | :12:33. | |
minutes, they take three grand in cash, cigarettes and alcohol. | :12:34. | :12:38. | |
Detectives believe the game comes from south-east London, and so the | :12:39. | :12:42. | |
gun has not been found. Were you on old road in Dartford that night? Did | :12:43. | :12:47. | |
you see these men running away from the shop? We need to know. November | :12:48. | :12:55. | |
last year, and two men appear to be having words in a West London | :12:56. | :12:59. | |
bookies. But things turn heated as one is pushed across the room into a | :13:00. | :13:05. | |
doorway. The scuffle is broken up, but moments later, the man in the | :13:06. | :13:09. | |
cap hits the other punter, knocking him into a gaming machine, which | :13:10. | :13:15. | |
falls over. Still on the ground, the victim is punished again. He seeks | :13:16. | :13:21. | |
refuge at the back of the shop, while his attacker rants and raves. | :13:22. | :13:25. | |
He keeps up his Thai raid until eventually he calms down and walks | :13:26. | :13:37. | |
out. -- he keeps up his tirade. If you know any of those crooks, get in | :13:38. | :13:39. | |
touch. Now to | :13:40. | :13:42. | |
a concerned onlooker who ended up It has affected me terribly. I keep | :13:43. | :13:55. | |
re-enacting it, that is the trouble. Thinking of all of the things I | :13:56. | :13:57. | |
should have done differently. On his way home from work one night | :13:58. | :14:11. | |
in March, Paul Grub got off the bus to pick up a takeaway. It is a | :14:12. | :14:17. | |
regular Friday night for me. That is what I usually do. I was looking | :14:18. | :14:23. | |
forward to having my Chinese and going home. Paul was minding his own | :14:24. | :14:35. | |
business at the bus stop when his night took a turn for the worse. A | :14:36. | :14:41. | |
card pulled up in front of me, and the man was smashing on the steering | :14:42. | :14:47. | |
wheel, raging in the car. He was obviously upset. He was in a proper | :14:48. | :14:52. | |
road rage. His girlfriend was frozen in the passenger seat. She wasn't | :14:53. | :14:56. | |
looking at him. She looked incredibly nervous. Then the driver | :14:57. | :15:01. | |
noticed that Paul was looking at him. I probably should have picked | :15:02. | :15:06. | |
up my takeout and moved away from the situation, but I was like a deer | :15:07. | :15:13. | |
in the headlights, looking at him. Without warning, the driver leapt | :15:14. | :15:17. | |
out of his car. The next thing I know, he dived out and punched me in | :15:18. | :15:19. | |
the face. he was doing. It was a straight left | :15:20. | :15:42. | |
to the right cheekbone. That was obviously something he knows how to | :15:43. | :15:47. | |
do. While Paul lay dazed on the pavement, the driver ran back to his | :15:48. | :15:52. | |
car and drove off at speed. I came home, I was bleeding a little bit. I | :15:53. | :16:00. | |
was obviously in a state of shock. I went to bed and when I got up in the | :16:01. | :16:03. | |
morning I could not see through my eye. That is when I went to | :16:04. | :16:10. | |
hospitals. This has affected me and I feel sorry for other people who | :16:11. | :16:16. | |
aren't as tough as me. It has upset me, it is a living hell. It has | :16:17. | :16:23. | |
taken some getting over. Police want to know who is responsible for this | :16:24. | :16:28. | |
attack on an innocent bystander. He has taken all his anger out on | :16:29. | :16:33. | |
Paul. It was an unprovoked attack and he did not deserve that. He is | :16:34. | :16:40. | |
described as a mixed race mail. Early 20s. About five foot six. The | :16:41. | :16:49. | |
car, we believe is a silver VW, either a golf or a polo but it is a | :16:50. | :16:55. | |
BW golf, polo style car. Police want to talk anybody he was in the | :16:56. | :16:59. | |
attack's car that night. Particularly the woman in the | :17:00. | :17:06. | |
passenger seat. She knows what went on. What has happened to me, I have | :17:07. | :17:12. | |
to deal with. But she has to deal with that man's rage. I hope she can | :17:13. | :17:18. | |
cope with it. If she can't, she should get in touch with it. She | :17:19. | :17:22. | |
knows who this man is and she knows why he was so angry and she might | :17:23. | :17:30. | |
know why he vented his anger out on Paul. We would appreciate if she | :17:31. | :17:33. | |
came forward and told as who this individual was and why he was so | :17:34. | :17:39. | |
angry on this day. Paul has yet to recover from this assault. I could | :17:40. | :17:45. | |
not believe anybody would just jump out of the car and punch somebody. | :17:46. | :17:49. | |
It is shocking. It is unbelievable you would just do that. It has | :17:50. | :18:07. | |
butted me. -- gutted. I would like to say to your man, he has punched a | :18:08. | :18:19. | |
63-year-old man in the face. When he is digging it up, I would like to | :18:20. | :18:22. | |
remind him that is who it was he punched. Sargeant Neata Simpson is | :18:23. | :18:34. | |
leading this investigation. The car is important, what is it you are | :18:35. | :18:39. | |
looking for? It is a Silver Volkswagen goal. There was a | :18:40. | :18:45. | |
passenger in the front, but you think there could have been more | :18:46. | :18:51. | |
people who could help you? Two passengers in the rear of the | :18:52. | :18:58. | |
vehicle. 28th of March, 11 B -- 11pm, Harborne, a busy part of | :18:59. | :19:03. | |
Birmingham, shops and people might be out and about. What direction was | :19:04. | :19:09. | |
that are heading off in? We believe people would have seen the vehicle | :19:10. | :19:15. | |
on the high street and it made off at speed towards Birmingham City | :19:16. | :19:23. | |
centre. Anybody who saw that car leaving Harbourne High Street on the | :19:24. | :19:29. | |
28th of March around 11 o'clock, please get in | :19:30. | :19:36. | |
We've still got a lot to bring you on this Tuesday morning. | :19:37. | :19:40. | |
We'll be putting a state-of-the-art plastic gun | :19:41. | :19:43. | |
we are dealing with somebody who looks like Friar Tuck. I see him | :19:44. | :20:01. | |
running over the road time and time again. | :20:02. | :20:15. | |
These might not be the uniforms you would expect to see in a police | :20:16. | :20:23. | |
station in Birmingham but these officers are a key part of this | :20:24. | :20:28. | |
operation. They are working alongside British police in this | :20:29. | :20:30. | |
week-long initiative targeting cross-border crime. Today we are | :20:31. | :20:38. | |
joint by two officers. One from Romania and one from Poland. We are | :20:39. | :20:45. | |
doing stop checks. Within minutes, the constable spots a hatchback he | :20:46. | :20:52. | |
wants to investigate. It is a foreign registered number plate. | :20:53. | :20:57. | |
Just going to see if it has insurance and what kind of license | :20:58. | :21:01. | |
this individual is driving on as well. Where do you live? We will | :21:02. | :21:12. | |
follow you. All the documents are in order and he is sent on his way. | :21:13. | :21:25. | |
This is just one of as many as 30,000 foreign registered vehicles | :21:26. | :21:26. | |
on UK roads at any one time. This operation is about helping police to | :21:27. | :21:28. | |
identify those being driven here illegally or being used by | :21:29. | :21:32. | |
criminals. It is about targeting criminality and not the community. | :21:33. | :21:37. | |
Most people who come over want to have a better life. I want to earn | :21:38. | :21:40. | |
money and pay their taxes and support their families at home. The | :21:41. | :21:49. | |
team are still out searching for any vehicles from European countries. | :21:50. | :21:54. | |
They spot a car with Romanian plates and go to investigate. Is it your | :21:55. | :22:08. | |
car? My cousin's car. This is where the cooperation between forces | :22:09. | :22:11. | |
really pays off. They step into question the driver in his own | :22:12. | :22:18. | |
language. Then a quick call to his colleagues in Romania reveals this | :22:19. | :22:30. | |
driver should not be on the road. This vehicle has no insurance so | :22:31. | :22:33. | |
this man is committing offences over here. The officers also doubt | :22:34. | :22:40. | |
whether his licence is genuine. This does not look real. You are under | :22:41. | :22:46. | |
arrest on suspicion of having a forged document. Basically I don't | :22:47. | :22:52. | |
believe that license is real and you are arrested for no insurance as | :22:53. | :22:58. | |
well. It goes to show how well this works because we cannot clarify if | :22:59. | :23:03. | |
he has or has not got insurance. If these officers were not here, he | :23:04. | :23:07. | |
probably would be still driving around on the roads with no | :23:08. | :23:12. | |
insurance. Although the police dropped any allegations the driver | :23:13. | :23:16. | |
had faked documents he was then found guilty and fined for driving | :23:17. | :23:24. | |
with no licence and no insurance. The operation has been hugely | :23:25. | :23:27. | |
successful. We have stopped over 3500 vehicles and just short of 200 | :23:28. | :23:34. | |
arrests in a five-day operation and targeting those criminals was passed | :23:35. | :23:39. | |
of the objective of this particular operation. Superintendent Paul Casey | :23:40. | :23:45. | |
has come to joiners. Staggering statistics in that film. Huge | :23:46. | :23:52. | |
success? It was. What was incredible was not only the volume of vehicles | :23:53. | :23:58. | |
we stopped, but the 370 vehicles we seized, arrests, and also what was | :23:59. | :24:05. | |
important and part of the main object of this, 1100 new pieces of | :24:06. | :24:11. | |
intelligence we obtained involving foreign national and organised crime | :24:12. | :24:18. | |
groups. There was an excavator worth about ?160,000 and cigarettes. If | :24:19. | :24:23. | |
you have not got those off the streets, they could have been | :24:24. | :24:31. | |
dangerous? This was a public health concern, who knows what was | :24:32. | :24:36. | |
contained in those cigarettes. Why so vital you are working with | :24:37. | :24:41. | |
colleagues from Eastern Europe? We had colleagues from Romania, | :24:42. | :24:45. | |
Lithuania and Poland and it is about sharing intelligence and getting | :24:46. | :24:50. | |
that information and translating it into activities on the ground. All | :24:51. | :24:54. | |
44 forces in the UK took part in this. Intelligence is a word you are | :24:55. | :25:00. | |
using over and over again, it wasn't just about stop and search? No, it | :25:01. | :25:08. | |
is about tackling criminality and not the community. It is important | :25:09. | :25:13. | |
we have intelligence behind everything we can do to maximise | :25:14. | :25:16. | |
results. It is not just weapons or drugs | :25:17. | :25:20. | |
criminals will go to great lengths to get across borders, the trade in | :25:21. | :25:24. | |
species is big business to traffickers. But pioneering | :25:25. | :25:30. | |
scientists are using cutting edge techniques to hold wildlife | :25:31. | :25:34. | |
criminals. One of those scientists is Dr Natasha de Vere. What is this | :25:35. | :25:41. | |
project you are working on? Fighting wildlife crime using bar-coding. We | :25:42. | :25:47. | |
can use it to identify part of animals from Tony pieces. Poaching | :25:48. | :25:56. | |
is a massive issue. We can see some elephants and some of the elements | :25:57. | :26:05. | |
-- animals you want to protect? In Africa in 2013, 20,000 elephants | :26:06. | :26:10. | |
were poached. It is not sustainable, at the birth rate is lower than the | :26:11. | :26:15. | |
amount being killed. We can see some of the ivory being made into | :26:16. | :26:18. | |
furniture or something like that, but some people think animals have | :26:19. | :26:27. | |
bizarre medical qualities? Rhino horns, tiger bones, people think it | :26:28. | :26:34. | |
has properties that kills cancer. It doesn't, it has no value, apart from | :26:35. | :26:41. | |
on the animal. You only need a small sample of these animals or plants to | :26:42. | :26:47. | |
extract DNA. These are some of the samples but you think they are big? | :26:48. | :26:52. | |
You really do need a tiny, tiny fragments and you can get DNA to | :26:53. | :26:58. | |
identify. You could use this with border control if people are trying | :26:59. | :27:03. | |
to smuggle out something that is round-up and not obvious. They can | :27:04. | :27:08. | |
test it and match it up and see if it is endangered from that? The key | :27:09. | :27:12. | |
thing is to have a reference database. You take the plants and | :27:13. | :27:22. | |
animals that you know, take an unknown sample, match it and make an | :27:23. | :27:31. | |
identification. So far, where have you been? Been to Kenya. Not long | :27:32. | :27:40. | |
back from Kenya. This is with the guys in Kenya. They are trained | :27:41. | :27:42. | |
scientists and we go out and work out protocols that can be used in a | :27:43. | :27:44. | |
court of law. Now they can do that on their own and you can leave them | :27:45. | :27:48. | |
to it now they are trained? That is correct. Going to Mexico on Saturday | :27:49. | :27:54. | |
so that will be the next couple of weeks. Then those countries will be | :27:55. | :27:58. | |
carrying on the process over the coming years. It is a fantastic | :27:59. | :28:05. | |
project. For now, let's go to Sian in the West Midlands. | :28:06. | :28:10. | |
We are looking at the work of NABIS in taking guns off the streets. This | :28:11. | :28:19. | |
is in the armoury and that is why this location has to be kept top | :28:20. | :28:24. | |
secret. There are 1500 weapons in here from handguns to rifles. We can | :28:25. | :28:32. | |
find out more about the work of NABIS, by Detective Chief | :28:33. | :28:37. | |
Superintendent Iain O'Brien. What were you doing here? It is critical | :28:38. | :28:45. | |
for policing, it helps an investigating officer to understand | :28:46. | :28:50. | |
if the gun has been used previously in crime. We gain intelligence from | :28:51. | :28:53. | |
that examination which tells as if the gun can be linked to other crime | :28:54. | :29:01. | |
scenes, which is pivotal when you are making decisions. And we see | :29:02. | :29:11. | |
trends at NABIS from doing those examinations and we can understand | :29:12. | :29:14. | |
whether we need to change legislation or influence legislation | :29:15. | :29:15. | |
with the government. These ones have an interesting story? This is a 1911 | :29:16. | :29:20. | |
Saint Etty and revolver. A weapon like this was used during the | :29:21. | :29:25. | |
disorders in Birmingham in 2011 and was seized as part of the | :29:26. | :29:27. | |
investigation into the shooting of the helicopter in the West Midlands | :29:28. | :29:34. | |
Police area. It is an anti-but a lethal weapon. You are talking about | :29:35. | :29:40. | |
changes into legislation, and it will be tightened up even further? A | :29:41. | :29:46. | |
trend we have identified is antique guns have been used by criminals. | :29:47. | :29:52. | |
Antique collecting of firearms is a legitimate pastime. But those self | :29:53. | :29:59. | |
loading pistols used in the First World War, that is the modern | :30:00. | :30:02. | |
version and there is very little difference between those weapons and | :30:03. | :30:06. | |
that is the dilemma. It has been fascinating. Many of the weapons | :30:07. | :30:13. | |
have come from different routes, and some of you believe have been found | :30:14. | :30:22. | |
in houses, heirlooms dating back to the Second World War is and the | :30:23. | :30:25. | |
families have found them and taken them down to the local police | :30:26. | :30:31. | |
station. That is the past, now let's head to the future and talk to Simon | :30:32. | :30:34. | |
about our 3-D gun. How are things going? The barrel has just finished | :30:35. | :30:54. | |
printing. And these can be incredibly dangerous, and illegal. | :30:55. | :30:58. | |
We have some filming showing a test-firing. Talkers through what | :30:59. | :31:04. | |
happened. That one was produced in a way that someone might do if they | :31:05. | :31:09. | |
had a printer at home, and when the trigger was pulled, the end of the | :31:10. | :31:12. | |
barrel exploded and parts went everywhere. That would be dangerous | :31:13. | :31:17. | |
to the person holding the gun. Thank you for showing us that this | :31:18. | :31:21. | |
morning. Even though these are plastic, they can be incredibly | :31:22. | :31:24. | |
dangerous, and they need to be detected. We will be looking at that | :31:25. | :31:26. | |
later. Now would you recognise a man with | :31:27. | :31:29. | |
a distinctive haircut? Police believe it's key to | :31:30. | :31:32. | |
tracking down a serial mugger. For a long time, I have thought | :31:33. | :31:41. | |
about him, I have seen him in my mind. To pick on elderly ladies like | :31:42. | :31:50. | |
this is despicable. Jean lives in Coventry, and at 84 years old, is | :31:51. | :31:58. | |
both active and independent. Early in March this year, she was on her | :31:59. | :32:03. | |
way to get her hair done as she did every month. Because it was such a | :32:04. | :32:08. | |
lovely day, I decided to walk to the headdresses. Always the same | :32:09. | :32:15. | |
hairdresser. I have been going there for 20 years. I came out of there | :32:16. | :32:22. | |
about one o'clock. Leaving the hair dresser, Jean walked back along a | :32:23. | :32:28. | |
stretch of pavement shielded from the road by trees. It was very | :32:29. | :32:32. | |
quiet. Sometimes there are people in their gardens, but there were no | :32:33. | :32:36. | |
people about at the time. I didn't see anyone until someone just | :32:37. | :32:41. | |
suddenly pounced. Without warning, her handbag was snatched. It was | :32:42. | :32:48. | |
such a shock, suddenly someone grabbed my bag off my shoulder. I | :32:49. | :32:58. | |
just screamed, no, no! And away he had gone. He was seen running from | :32:59. | :33:06. | |
the scene, rifling through the bag. Items were discarded as he ran from | :33:07. | :33:12. | |
the scene. Gene is not alone. Police believe the same man is responsible | :33:13. | :33:19. | |
for seven similar attacks. All of these crimes took place between 10am | :33:20. | :33:23. | |
and 1pm in a tight geographic grouping around that area of | :33:24. | :33:29. | |
Coventry. The crimes all had a massive impact on the victims as a | :33:30. | :33:32. | |
result of them being elderly victims, the oldest was 89. The | :33:33. | :33:38. | |
victims of this Munger have been left to deal with the shock and pick | :33:39. | :33:42. | |
up the pieces. I couldn't get into my own house because the keys were | :33:43. | :33:47. | |
in the bag that he had stolen. I had to have the locks changed | :33:48. | :33:50. | |
immediately on the door. Cancel my mobile phone. My bus pass was in | :33:51. | :33:58. | |
there, my driving licence. So much trouble that it causes you. If only | :33:59. | :34:02. | |
these people realised what they are doing. Jean's daughter Tracy has | :34:03. | :34:07. | |
seen just how much the attack has affected her mum. She came and | :34:08. | :34:13. | |
stayed with us that evening and for a few evenings after that, because | :34:14. | :34:18. | |
she was quite shaken by it all. For a long time, I have thought about | :34:19. | :34:22. | |
it, thought about him, seen him in my mind. I could see him running | :34:23. | :34:29. | |
across the road. Over and over again. Police are looking for a man | :34:30. | :34:32. | |
with a very distinctive and pronounced bald patch. The hair has | :34:33. | :34:39. | |
been described as quite short, dark brown or black, and balding around | :34:40. | :34:42. | |
the crown of the head, similar as one witness describes to a Friar | :34:43. | :34:49. | |
Tuck hairstyle. Gene is still coming to terms with what happened to her. | :34:50. | :34:53. | |
This is the last thing I would have expected walking along the footpath, | :34:54. | :34:57. | |
almost home. I hadn't seen anyone lurking about, but he had obviously | :34:58. | :35:05. | |
seen me. If they could catch him, I would feel safer for my mum and | :35:06. | :35:08. | |
anybody else elderly around the area. He was choosing elderly | :35:09. | :35:15. | |
ladies, easy pickings. I hope that he gets his comeuppance. | :35:16. | :35:22. | |
And I'm joined now by Detective Inspector Gareth Mason, who has | :35:23. | :35:25. | |
You're confident that the same person carried out these attacks? | :35:26. | :35:33. | |
It is unusual to have robberies in this area, and based on the fact | :35:34. | :35:38. | |
that it is lone females, all targeted at the same time of day, | :35:39. | :35:41. | |
all with the descriptions matching, suggested is the same offender. And | :35:42. | :35:46. | |
you think he could be local? Absolutely. The way that the | :35:47. | :35:51. | |
offender has moved as described by the witnesses, tight geographic | :35:52. | :35:58. | |
location, same kind of day, all suggest is local. He has been | :35:59. | :36:04. | |
described as white, in his 30s, five foot eight. His hair is short and | :36:05. | :36:10. | |
dark, balding around the crown, and it has been described as looking | :36:11. | :36:15. | |
like Friar Tuck. That is pretty distinctive. Do you think he could | :36:16. | :36:19. | |
strike again? There has been no offence since the beginning of | :36:20. | :36:22. | |
March, and hopefully that will carry on, but some witnesses described him | :36:23. | :36:29. | |
as having an appearance like a drug or alcohol addict, so he made a | :36:30. | :36:33. | |
chaotic life and may strike again. Thank you very much. | :36:34. | :36:37. | |
Now I'm joined by DC Jolene Podmore from Gwent Police who needs | :36:38. | :36:39. | |
your help to stop a very cheeky car thief. | :36:40. | :36:42. | |
Now this car thief has got a very specific way of working, hasn't he? | :36:43. | :36:45. | |
He turns up at garages and asks to test drive a car. | :36:46. | :37:00. | |
It is usually a garage, they attend as a couple and speak to the owner. | :37:01. | :37:11. | |
It's usually an Audi, Golf, BMW or Mercedes he asks to drive. | :37:12. | :37:13. | |
He gives false ID to get the garage to let him test drive the car | :37:14. | :37:17. | |
before then driving off and neither he or the car is seen again. | :37:18. | :37:22. | |
They are typically high-value cars. Yes, that's right. And on one | :37:23. | :37:33. | |
occasion, the audacity is unbelievable, Wattie Atchley did. | :37:34. | :37:36. | |
Tell me about that. Slightly different on this one. They arrived | :37:37. | :37:45. | |
at a garage and asked to test drive an Audi. They went for a very short | :37:46. | :37:58. | |
test drive. Then the male hands back the key to a garage owner, but it is | :37:59. | :38:02. | |
actually a false key, he switches them. The garage owner goes out into | :38:03. | :38:07. | |
his office, but an hour later, they come back and drive the car away. | :38:08. | :38:14. | |
They have been caught on CCTV. This is the fellow you want to identify. | :38:15. | :38:19. | |
This is the mail we want to identify and locate. He is approximately six | :38:20. | :38:32. | |
foot tall, in his late 30s. He and the woman with him both have very | :38:33. | :38:38. | |
strong Welsh Valley accidents. And we have an image of the woman as | :38:39. | :38:43. | |
well. This is her. She is in her mid-20s, quite a bit younger. She | :38:44. | :38:48. | |
has dark hair, and again, a strong Welsh Valley accident. And it is not | :38:49. | :38:56. | |
just a small area, this is all over. You are advising garage owners to be | :38:57. | :39:00. | |
on the lookout and to get in touch as well. That's right. Thank you | :39:01. | :39:03. | |
very much for joining us. Well, if you know who this brazen | :39:04. | :39:10. | |
duo are, then you know what to do. Get in touch using the numbers | :39:11. | :39:14. | |
on screen. Or you can call Crimestoppers | :39:15. | :39:16. | |
anonymously on 0800 555 111. We saw that 3-D gun being created, | :39:17. | :39:33. | |
and even though it is plastic, it has to be detected. And the | :39:34. | :39:39. | |
technology for that has been developed here at NABIS. You have | :39:40. | :39:43. | |
brought all of the kits today, and we have four volunteers who have | :39:44. | :39:48. | |
agreed to take part. One of them is carrying a plastic gun, and we are | :39:49. | :39:51. | |
going to test and find out which one very shortly. But first of all, talk | :39:52. | :39:59. | |
is through the kit. It is a radar system that was developed in | :40:00. | :40:01. | |
conjunction with the Metropolitan Police Service. They wanted a stand | :40:02. | :40:07. | |
of gun detector. This is probably the first capability of the type. It | :40:08. | :40:11. | |
works rather like the radar gun using the police using on the | :40:12. | :40:13. | |
streets when they are measuring the speed of cars. It sends a very low | :40:14. | :40:18. | |
powered beam of microwaves towards the target, the person you are | :40:19. | :40:22. | |
trying to screen, looks for the reflections and analyses them on the | :40:23. | :40:25. | |
computer for what it perceives are either threat items, guns, | :40:26. | :40:32. | |
improvised explosive device is, and it tries to reject things like | :40:33. | :40:35. | |
mobile phones and keys because every body has those. It is try to work | :40:36. | :40:42. | |
out whether it is threat or no threat. An impressive piece of kit, | :40:43. | :40:46. | |
and it can see through clothes. Let's have a look at it in action, | :40:47. | :40:49. | |
and talkers through what is happening here. We need to find out | :40:50. | :40:55. | |
which person is carrying the gun. It is interesting though, we can see | :40:56. | :40:58. | |
the images on the screen as well as the gun can slowly check out each | :40:59. | :41:06. | |
person here. The radar beam is overlaid on top of a normal image, | :41:07. | :41:11. | |
see you can see wave screening. It can see through the clothing. The | :41:12. | :41:19. | |
image can't, obviously. We can try to identify where there is a likely | :41:20. | :41:24. | |
threat. And no danger for anybody there. If you are worried about | :41:25. | :41:29. | |
mobile phones come you shouldn't be. This is thousands of times less in | :41:30. | :41:32. | |
terms of the power it outputs than a mobile phone. It is barely | :41:33. | :41:37. | |
detectable. We saw it turn red there. Can the person in the grey | :41:38. | :41:43. | |
suit with the pink tie step forward, please. And are you carrying the | :41:44. | :41:52. | |
gun? Yes. Let's have a look. The technology in action. Thank you all | :41:53. | :41:56. | |
for taking part, and thank you for explaining it. | :41:57. | :42:01. | |
Russell brought in, who police want to it speak to, police are following | :42:02. | :42:10. | |
up a positive lead. And another one of our Faces, wanted in connection | :42:11. | :42:15. | |
with a distraction burglary, great information about him this morning. | :42:16. | :42:18. | |
Plus you remain remember last week that we showed you footage of a lady | :42:19. | :42:25. | |
in a wheelchair who was burgled at a department store. Positive sounding | :42:26. | :42:28. | |
new leads from that case. Thank you to every single one of you who has | :42:29. | :42:30. | |
got in touch. Now, Sian, where are you | :42:31. | :42:33. | |
and the team heading to next? Rav, tomorrow takes me back home as | :42:34. | :42:36. | |
we join Wales' biggest police force. I'll be in South Wales finding | :42:37. | :42:39. | |
out how emergency crews are being hindered by the very | :42:40. | :42:44. | |
people they are trying to help. And there'll be more fraudsters | :42:45. | :42:52. | |
caught in the act on BBC One in an hour, | :42:53. | :42:59. | |
stay tuned for Claimed and Shamed. If you want to find out how you can | :43:00. | :43:01. | |
help with any of the crimes on today's programme, | :43:02. | :43:05. | |
head to the website. Finally, let's take one last look | :43:06. | :43:06. | |
at those Wanted Faces. Do you recogonise anyone | :43:07. | :43:08. | |
in our rogues gallery? We're getting good results | :43:09. | :43:10. | |
already on this year's roadshow. We are about to find out whether | :43:11. | :43:14. | |
they can cook. You're going to love it. | :43:15. | :43:58. | |
Smashed it. Yum-yum-yum. | :43:59. | :44:02. |