3 massive technologies set to define the next few years

Last year saw some major technological advances in industry and further developments on the smart factory front. It was a year that demonstrated 3D printing’s potential as more than just a prototyping method and saw cloud computing capabilities stretched and broadened as more companies sought to analyse and exploit big data.

The list wouldn’t be complete without mentioning the Internet of Things (IoT). Greater convergence allowed the creation of more intelligent networks in which machines are able to communicate with each other and perform self-diagnostics with minimum human interaction. On top of all of this, last year also brought forth the world’s first internet-enabled toothbrush.

Many are safely predicting these same trends will go from strength to strength in 2015. But what other technologies should we be looking out for this year?

Wearables

Wearable tech has been around for a while, but with the Apple watch being released in April 2015, this could be the year it really takes off.

The UK Home Office, for example is interested in exploiting the capabilities of the latest wearable technologies and equipping British police officers with cutting-edge Robocop-style gear. Google Glass and other wearable devices should give law enforcement officers more information at their fingertips — or eyelashes — when they’re out on patrol. Exoskeletons like the ones already being tested by the US military will take the strain of heavy gear and give added support to joints when walking the beat.

A similar idea recently caught the attention of Daewoo Shipbuilding and Marine Engineering. The company prototyped a robotic exoskeleton to help shipbuilders lift heavy weights. The wearable robotic suits are made of light-weight aluminium alloy and steel and are engineered to follow the wearer’s every movement. In their current prototype stage Daewoo’s exoskeletons can help workers lift up to 30 kg, but the creators believe that they can increase the weight to a potential 100 kg.

Straps at the feet, thigh, waist and chest connect the user to the suit and allow the exoskeleton to move with the wearer and bear the heavy loads. A system consisting of hydraulic joints and small electric motors runs along the outside of the leg linking to a backpack, which powers and controls the equipment.

A subsidiary of Panasonic has also developed a similar robotic suit designed to aid lifting and promote fluid movement. The company plans to mass-produce and sell their exoskeleton in 2015 and so this year could very well see robotic support aids used more widely than just the medical sector.

With all of this happening, you have to wonder how long it will take before wearable technology enters the modern factory. The days of sitting at a static HMI are over – with the IoT and wearable devices, workers can be fluent, mobile and always on the ball.

Quantum entanglement

Quantum entanglement describes the surprising interactions among subatomic particles and was dispelled as ‘spooky’ by Albert Einstein. We all know that a camera captures light that bounces back from an object. But a recent experiment showed that light particles – or photons – that never strike an object can still produce its shadow in a demonstration of a strange quantum connection with those that do. This is because they all have to share wavelength phases with the light that hits the object, which we can then detect to see the picture.

This is a particularly tricky idea to understand fully, but essentially it means that information could be teleported across short distances. Using this method a new imaging technique could be developed for improved medical imaging in hard to see areas. Harmless and invisible beams of light could be passed through tissues whilst simultaneously creating an image with entangled visible light.

Quantum entanglement isn’t quite as exciting as teleportation, but it’s an amazing discovery that could inspire some innovative applications for industry.

Deep learning

Deep learning refers to complex algorithms that allow computers to emulate human thinking, for example seeing something and understanding what it is. There are already applications that utilise deep learning like the app created by startup Partpic. The app allows you to immediately scan and identify spare parts without barcodes or labels. Say a motor breaks down in a factory and lacks exterior identification tags; you would simply scan the part with the app and it will recognise the model and bring up a list of suppliers.

Large companies with vast data archives will probably be particularly keen to extract value from deep learning applications. To do so, terabytes of information will have to be processed by computers at a very speedy pace to determine what’s useful and what isn’t.

Is this the end?

There’s a good chance that a few of the things mentioned in this article won’t fully come to fruition in 2015, but much later down the line. However, as Malcolm X once said, “the future belongs to those who prepare for it today.” Higher levels of automation in manufacturing are being achieved from every year and in some cases, it’s those willing to take a bit of a risk that will reap the greatest rewards.