IoT ruins movies: The Thomas Crown Affair

By | 3 minute read | December 5, 2017

‘Tis the season to be sickly, so I spent Friday afternoon watching The Thomas Crown Affair through a haze of phlegm and self-pity. The 1999 one, not the 1968 one. Yes, it still counts as work. And the reason is that, fortunately, this Pierce Brosnan-y classic is terrific fodder for IoT ruination. Below, we delve into the shady…shades… (what? I’m poorly) of forgery, theft, and even a Trojan horse.

The movie: The Thomas Crown Affair

The Thomas Crown Affair is a suave remark of the 1968 American heist of the same name, directed by John McTiernan. Pierce Brosnan stars as billionaire Thomas Crown, the surprising culprit behind the theft of a priceless Monet, which he pinches from the Metropolitan Museum of Art. Catherine Banning (Rene Russo) is sent by the artwork’s insurers to investigate the theft, and realizes Crown is behind it. Somewhat inconveniently, the pair fall in love. Nonetheless, she decides to report him to the authorities, who lie in wait for him at the museum. With the help of accomplices, identically dressed as the ‘faceless businessman’ in suit, bowler hat and briefcase, Crown bamboozles the police and orchestrates an escape that’s as elegant as you could wish.

How the IoT could ruin the movie The Thomas Crown Affair

There’s ruination potential aplenty in Thomas Crown Affair, covering many an IoT-related base. Connected buildings, smart curation, IoT asset management systems and machine learning all have a part to play. Here’s how:

#1: An IoT asset management system would have bested the Trojan horse

In an early scene, a bemused foreman takes delivery of an ‘Asia Greco Horse’ when he’s expecting a sarcophagus. Those of you paying attention will have spotted the joke already – the horse is less priceless artefact than cheap plaster molding, in which three cramped burglars are hiding, spilling from it like popes from a Volkswagen once the coast is clear.

With an enterprise asset management system like IBM Maximo, it would have been possible to track each valuable shipment thanks to connected sensors that broadcast its location. The foreman would have received updates to a handy dashboard telling him where the sarcophagus had gone astray. He would also have been able to check the origin of the unexpected horse with other parties in the supply chain, and realized it was a suspicious item.

#2: There’s no fooling the cameras in a connected building

In the film, the Metropolitan Museum of Art uses thermal imaging camera to keep track of visitors’ movements even in failing light. Unfortunately, once the temperature in the room rises above 90F, the cameras can’t distinguish bodies from anything else, and become essentially useless. Knowing this, and not wanting to be filmed taking the Monet, Thomas Crown surreptitiously places a suitcase containing a heater underneath the bench, to raise the temperature of the room and prevent the cameras from working properly.

A connected building would have used temperature sensors to monitor each room, and activated an automatic cooling system once the temperature passed a certain threshold. If the cooling system failed, there could be other contingencies in place: swapping from thermal imaging to ordinary security cameras, for instance.

#3: Forgery detection

Catherine Banning enjoys a brief moment of triumph when she tracks down what appears to be the stolen Monet. Unfortunately, it’s a fake. An expert, peering down a high-powered microscope, discovers a ‘ghost’ underneath the painting that certainly post-dates Monet.

Here, Artificial Intelligence and machine learning could speed up the process of forgery detection. Researchers from Rutgers University and the Atelier for Restoration & Research of Paintings in the Netherlands have released a paper, documenting a new system from breaking down paintings and drawings into thousands of individual strokes. Using cognitive computing, the system identifies features in individual strokes belonging to specific artists. Machine learning capabilities can then be used to search for specific features, such as a stroke’s shape, or the length of the line.

Such minute analysis, much of it almost invisible to the naked eye, makes getting away with forgery almost impossible, and considerably speeds up the process of detection.

The tech behind the tales: find out more

If you’re interested in some of the technology mentioned above, you might enjoy these web resources:

Meanwhile, we’ve been busy ruining lots of movies for your enjoyment. If you can think of others that deserve the same treatment, give us a shout in the comments below.