May 17, 2020

Transportation 4.0: Multimodal transportation systems

Multimodal transportation systems
Internet of Things
Roch Muraine
5 min
Transport systems
Whether it’s keeping up with work while on the move, staying in touch with co-workers and friends, or just looking for some entertainment, travelers w...

Whether it’s keeping up with work while on the move, staying in touch with co-workers and friends, or just looking for some entertainment, travelers want to stay connected. Now, this demand is spreading to the transportation systems themselves.

The technology to create seamless or connected multimodal transportation exists, but the majority of services are still being delivered to the end customer in a disconnected, piecemeal way. For example, a journey from A to B might involve switching from a bus to a train and then a ferry, with tickets purchased for each separate stage from the different operators providing transportation. In order to improve services and keep up with the huge growth in numbers of people traveling throughout the world, we need to look at new ways to streamline services for travelers and simplify the provision of services for operators.

Transportation 4.0 explained

All things point to a future that lies in multimodal transportation, where different forms of transportation are integrated into a single passenger interaction to arrange complete door-to-door travel. Imagine buying one ticket to get you on a train, to the airport and straight to the hotel – where your luggage will be waiting for you. The aim is to make travel experiences more efficient, safer, greener and less hassle while optimizing journey times, and minimizing costs for travelers. We are just now starting to see how this future might develop, with the potential to completely transform travel.

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The connected experience – we’re already on our way

The multimodal experience starts at home or on your smartphone. There are already travel planning apps and websites that show different modes of transportation, times and costs to help get passengers from A to B, but even these are done through separate providers and intermodal systems. In the future, we will see services that will be able to book your whole itinerary through a single app - with one search and payment.

Smart-ticketing and e-ticketing are essentially already here. From boarding passes on smartphones to contactless card machines on buses, the next step will be to offer one ticket for all forms of travel. While simplifying travel for passengers, these ticketing systems are also useful to transportation operators as information gathered by smart systems can be analyzed to offer better services.

Single token travel is the next development in multimodal travel—using a passenger’s biometrics and travel data to create a digital record and provide secure authentication. The technology has the potential to create a seamless journey for passengers by cutting the time taken for security checks, check-in and boarding at airports and stations.

In order to achieve multimodal travel, transportation systems need to be connected both physically and operationally. This means having the right infrastructure supported by high-quality, real-time information systems for connecting routes, schedules and fares.

Keeping passengers connected

Communication is an important factor in the passenger journey – keeping passengers connected and informed improves their experience. Smartphones, laptops and tablet devices are ubiquitous for travelers now, as is public Wi-Fi – the same needs to be true for real-time data and communications for transportation operators. In addition, there are applications that provide guidance and wayfinding to help find retail outlets, departure gates or even locate their car, but this is not enough. The real value comes from requesting assistance in real-time to enhance the passenger experience.

Collaboration services embedded in applications through a CPaaS (Communications Platform as a Service) model allow transportation authorities to provide real-time communications, such as messaging, voice and video, to provide scheduling updates, travel information, real-time interaction with staff and passengers and emergency notifications. All of this can be delivered via a single app, simplifying and enhancing the traveler experience.

Laying the groundwork with open data and APIs

Mass data is gathered every second from traffic management systems, CCTV cameras, vehicle detectors and many more devices, such as IoT - this will only increase in the future as transportation gets smarter. But collecting data is just one challenge. The real value comes from sharing data and creating operational processes to create truly connected transportation systems.

Infrastructure based on open data and APIs will be important to push forward future transportation innovations and mobility solutions. Multimodal transportation involves different operators coming together to provide better travel, but they can’t provide this without knowing what’s going on around them. Sydney Airport recently introduced an open data strategy that allowed it to offer an indoor Baidu Maps app to help passengers better navigate the airport’s terminals.

Safeguarding the network

Despite these benefits, security remains a challenge. The growth in the internet of things (IoT) and the increase in connected devices used by transportation operators in expanding networks will only increase the number of vulnerable points for unauthorized access – unless properly secured on the network. Cyber-attacks and data breaches are a top concern for IT departments right now, and it will be of vital importance that operators secure this data or risk losing passenger trust and the benefits of streamlined travel.

One solution to this problem is IoT containment, as part of an overall layered security approach. By ‘containing’ connected IoT devices into several virtualized environments on a network, businesses can greatly decrease the chances of a broad network breach, as the threat is confined and cannot spread to wider business operations. Using this segmented approach allows IoT devices to be managed and operated only by the authorized personnel that use them, simplifying IoT management.

Another security approach focuses on mission-critical communications, which has an important role to play in passenger security and operational safety. A consistent cybersecurity strategy is key to keep the communication platform safe from cyber-attacks and ensure service continuity, supported by embedded protection in the system and smart best practice rules.

A glimpse into the future

Multimodal transportation will completely transform the way we travel. The technology is already here, enabled by open APIs to offer a single ticket, payment and itinerary across different modes of transportation. But the groundwork – the network and systems that connect it all together - must be installed now if we are to take full advantage of seamless travel. This means having a secure and reliable network that keeps passengers and operators connected no matter what mode of transportation they’re using.

Roch Muraine, Global Sales Director, Transport, Alcatel Lucent

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Jun 11, 2021

Google AI Designs Next-Gen Chips In Under 6 Hours

3 min
Google AI’s deep reinforcement learning algorithms can optimise chip floor plans exponentially faster than their human counterparts

In a Google-Nature paper published on Wednesday, the company announced that AI will be able to design chips in less than six hours. Humans currently take months to design and layout the intricate chip wiring. Although the tech giant has been working in silence on the technology for years, this is the first time that AI-optimised chips have hit the mainstream—and that the company will sell the result as a commercial product. 


“Our method has been used in production to design the next generation of Google TPU (tensor processing unit chips)”, the paper’s authors, Azalea Mirhoseini and Anna Goldie wrote. The TPU v4 chips are the fastest Google system ever launched. “If you’re trying to train a large AI/ML system, and you’re using Google’s TensorFlow, this will be a big deal”, said Jack Gold, President and Principal Analyst at J.Gold Associates


Training the Algorithm 

In a process called reinforcement learning, Google engineers used a set of 10,000 chip floor plans to train the AI. Each example chip was assigned a score of sorts based on its efficiency and power usage, which the algorithm then used to distinguish between “good” and “bad” layouts. The more layouts it examines, the better it can generate versions of its own. 


Designing floor plans, or the optimal layouts for a chip’s sub-systems, takes intense human effort. Yet floorplanning is similar to an elaborate game. It has rules, patterns, and logic. In fact, just like chess or Go, it’s the ideal task for machine learning. Machines, after all, don’t follow the same constraints or in-built conditions that humans do; they follow logic, not preconception of what a chip should look like. And this has allowed AI to optimise the latest chips in a way we never could. 


As a result, AI-generated layouts look quite different to what a human would design. Instead of being neat and ordered, they look slightly more haphazard. Blurred photos of the carefully guarded chip designs show a slightly more chaotic wiring layout—but no one is questioning its efficiency. In fact, Google is starting to evaluate how it could use AI in architecture exploration and other cognitively intense tasks. 


Major Implications for the Semiconductor Sector 

Part of what’s impressive about Google’s breakthrough is that it could throw Moore’s Law, the axion that the number of transistors on a chip doubles every five years, out the window. The physical difficulty of squeezing more CPUs, GPUs, and memory on tiny silicon die will still exist, but AI optimisation may help speed up chip performance.


Any chance that AI can help speed up current chip production is welcome news. Though the U.S. Senate recently passed a US$52bn bill to supercharge domestic semiconductor supply chains, its largest tech firms remain far behind. According to Holger Mueller, principal analyst at Constellation Research, “the faster and cheaper AI will win in business and government, including with the military”. 


All in all, AI chip optimisation could allow Google to pull ahead of its competitors such as AWS and Microsoft. And if we can speed up workflows, design better chips, and use humans to solve more complex, fluid, wicked problems, that’s a win—for the tech world and for society. 



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