Updated: Oct 9, 2018
Back in September Massive Analytic headed to Singapore as part of a delegation of eleven UK-based SME’s on a UK global innovation mission. The aim of the mission was to support UK-Singapore partnerships in urban infrastructure and to build strategic partnerships between the two countries. On the back of the success of the first trip Founder & CEO George Frangou is returning to Singapore this month to continue talks and pursue further business opportunities.
Singapore is well known for being at the cutting edge of smart city innovations, ranking second globally in the 2017 Smart Cities Index by Easyparking. Their Smart Nation initiative aims to bring innovative technologies into all aspects of life, from healthcare, to government to transportation. This is their mission statement in their own words;
“The Smart Nation initiative is about harnessing the full power and potential of digital and smart technologies to create new jobs and business opportunities, in order to make our lives more convenient, and our economy more productive, through more efficient Government and business processes. But beyond that, a Smart Nation is about creating new opportunities in a digital age, and transforming the way people live, work and play, so that Singapore remains an outstanding global city.“
It’s impossible to predict with certainty what Singapore will look like in the future (even with artificial precognition) but all the time there are new and exciting examples of innovation that give us glimpses of what a future smart city might look like – and some of these concepts and innovations have a more personal interest for us.
For example, Singapore is one of the countries taking the lead in developing self-driving vehicles. In the summer of 2016, the Land Transport Authority (LTA) and JTC, in partnership with the Nanyang Technological University (NTU), launched CETRAN (Centre of Excellence for Testing & Research of AVs). Their testing at the CleanTech Park is putting Singapore right at the forefront of developing standards for driverless vehicles. This a major stepping stone for making self-driving vehicles road safe. The end goal is the development of apps to order driverless shuttles or pods for journeys as-and-when they are needed, essentially like a self-driving Uber service. It’s believed that this will drastically cut the number of cars on the roads in Singapore and the potential is of course for it to be applied to other cities around the globe. As someone who has lived his whole life in London easing congestion is near the top of my list as far as benefits go but there are others as well, such as providing mobility to an increasingly older and immobile population or reducing manpower costs for freight transportation to name just a few.
This is particularly interesting for us at Massive Analytic for a couple of reasons, the first is due to our links with Synthetik Mind, which is commercialising the patents behind our Artificial Precognition technology in driverless vehicles. The second is our continued work with Citi Logik. Urban analytics of the kind we’re working on with Citi Logik could form an important part in making driverless vehicles safe on the roads. The ability to have real-time insights on the positions of non-driverless vehicles, on footfall and predictions on the movement of the two in busy city centres can inform the AI moving the vehicle of which roads to take and which to avoid. Also depending on the kinds of safety standards that come into play self-driving vehicles may only be allowed on certain kinds of roads initially, Citi Logik’s location insight analytics will help inform decisions during the transition to having these vehicles on the road.
Another interesting innovation being concept trialled in Singapore is facial recognition, MINDEF (Singapore’s ministry of defence) is teaming up with Japanese company NEC to try their next generation facial recognition technology. Concept trials began in 2017 with this technology reportedly able to pick named individuals out of a crowd and detect suspect behaviour like loitering. The solution developed by NEC relies on a modified Generalized Learning Vector Quantization (GLVQ) algorithm together with an Intelligent Complex Event Processing engine which correlates audio and video analytics. Facial recognition technology has been around for a long time where this one differs is its ability to detect the “liveliness of a face”, previously facial recognition technology could be fooled by pictures and masks but apparently there’s no hiding from this one. Other suggested uses of facial recognition tech are easy hotel check ins and fare gates for trains that bill on monthly usage, showing the scope for this sort of technology outside the security and defence sectors.
Massive Analytic is also developing video analytics technology through our product Nethra. So far Nethra’s deep learning algorithms have been trained to recognise hundreds of different behaviours from video streams, however the step after that is where it gets exciting. Being able to recognise and flag dangerous behaviour or crime without needing excessive manpower to watch the security feeds is a big step forward for law enforcement – but that’s still reactive policing. The next step that we’re working on is developing the capability to be proactive, to spot the warning signs so that commanders can deploy resources to make the response time truly negligible. Our goal is for Nethra to be able to predict behaviour and notice dangerous patterns with greater accuracy and speed than is possible just with the human eye.
We’re very excited by the potential opportunities to collaborate and innovate with Singapore, so watch this space!