Spirent opens new research labs to explore autonomous car tech

Spirent opens new research labs to explore autonomous car tech

Spirent Communications is to open new research laboratories to explore and develop navigation technologies of the future.

Hardware, network and security testing company Spirent Communications has announced the opening of new research laboratories in Paignton, Devon, where sensors will be evaluated for their use in autonomous vehicles and new positioning technologies that use multiple signals such as Wi-Fi, LIDAR and RADAR, in addition to GNSS (global navigation satellite systems).  

The laboratories were officially opened by Professor David Southwood, chair of the steering committee at the UK Space Agency. “Seeing a company like Spirent working in space navigation, very much part of our future world, expanding its UK facilities is very exciting as the UK Space Agency works with industry to capture 10 percent of the global space market by 2030,” he said.

Read more: Cranfield University teams up with Spirent on connected car tech

The shape of things to come

Spirent, which is headquartered in Crawley, West Sussex, is apparently planning to increase all of its laboratories at its Paignton facility by over 50 percent in the next few years.

“Very few people realize that many of the high-tech devices we use every day have been tested by systems from Spirent in Paignton” said Martin Foulger, general manager of Spirent’s Positioning business unit.

“Our systems are widely used to test smartphones, infotainment systems in cars, fitness bands, drones, and many more devices, in addition to high-end applications such as aircraft and space vehicles. This expansion of our research facilities enables us to lead the development of test solutions for next-generation systems and maintain our global leadership position.”

The company claims that these new labs will underpin “next-generation” research activities and  also allow it to test systems to make GPS and other GNSS receivers more resilient to interference. This is a growing problem, according to Spirent, as increasing numbers of positioning, navigation and timing features are embedded in a wide range applications.

Read more: AEye unveils iDAR advanced perception and planning for driverless cars

Recruitment drive

The new labs also look set to bring new employment to an area of the country where it’s needed. “Over time, the additional laboratory space will enable Spirent to recruit more staff and increase its contribution to the local community,” said Caroline Lee, human resources director for Spirent. 

“The company is already very active in encouraging students to pursue STEM subjects – science, technology, engineering and mathematics – so the expanded facilities will help us to offer more opportunities in these areas,” she added.

In September 2017, the company teamed up with researchers at Cranfield University with a view to exploring ways to improve positioning and timing technologies for unmanned vehicles such as autonomous aircraft or connected cars.

Read more: UK government gives autonomous lorries the green light

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Robot swans to measure water quality in Singapore

singapore swan robots measure water quality on resevoirs

Robotic swans are being deployed in Singapore’s reservoirs to provide real-time assessments of water quality. The project is the culmination of work by the city state’s national water agency and the National University of Singapore.

Despite the best efforts of conscientious scientists, not all IoT solutions blend into their environments. Technology and utility tend to be prioritized over aesthetics. Unless you live or work near Singapore’s Marina, Punggol, Serangoon, Pandan and Kranji reservoirs, that is.

A joint project involving national water agency PUB, the National University of Singapore’s (NUS) Environmental Research Institute and the Tropical Marine Science Institute aims to gather data in a less conspicuous manner.

Read more: 100,000 IoT sensors line canal in China’s ambitious water diversion project

An elegant IoT solution

Designing a robotic swan that’s convincing to the human eye – albeit from a distance – is one thing. But the team behind the project has also fit each swan with all the tools it needs to move around reservoirs and sample water quality.

Using wireless technology, each swan is able to transmit live results to PUB, removing the need for teams to be sent out to take samples manually.

According to Channel News Asia, the SWAN project (Smart Water Assessment Network) will be used to monitor the City State’s fresh water pH, dissolved oxygen, turbidity and chlorophyll. All of these elements are used to determine the overall water quality.

Professor Mandar Chitre a member of the team behind SWAN from the National University of Singapore, said, “we started with a number of smaller bird models before we decided on the swan. It’s just the right size. If you look at it in the environment, it looks just like a swan swimming around.”

Read more: Underwater Antarctic robot Icefin prepares for Jupiter mission

Water-based robots combine with IoT once again

This is not the first time that scientists have looked to the natural world for inspiration when designing robots for use in water.

Last year, a similar project from EPFL in Switzerland developed a robotic eel to report on the water quality in Lake Geneva. Unlike the SWAN project, EPFL’s Envirobot was designed to mimic the movement of its real-life equivalent. But both have provided researchers with a way to measure water quality remotely.

With the addition of more data points and increased autonomy, it may not be long before more of these robots are spotted roaming our rivers, reservoirs and oceans.

Read more: Singapore companies settle on Sigfox for smart rodent control

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You are the weakest link, goodbye

George Malim worries that, as automation gathers pace, the single point of failure might turn out to be himself

Automation is gathering pace and, with the additional capabilities enabled by IoT, truly starting to deliver value and revenue to organisations. That’s great because it represents the promise of IoT becoming reality but there are substantial cultural and organisational challenges for businesses at the points where the automated hands over to the manual. In security, that’s the most likely point of failure – where human contact is introduced into the business chain but IoT systems seldom get to operate in complete isolation from humans.

I was recently discussing this with a colleague who had the opportunity to visit two supermarket retailers’ online shopping fulfilment warehouses. One was highly automated, utilising advanced systems to monitor supply levels and the performance of human stock pickers as they assembled customers’ shopping lists. The other was completely automated, with robots picking products and humans, in very small numbers, present only to respond to problems or maintain the robots. In such environments the lights don’t need to be on most of the time.

Whilst there’s a societal issue here in terms of reduced employment this fully-automated environment is enabling the retailer to accurately and efficiently serve the needs of its customers while maintaining an attractive margin. This will be replicated in more complex environments, hopefully freeing humans from the drudgery of repetitive tasks to be more productive in other ways. Certainly, if Bill Gates’ idea of taxing corporations based on their robot power instead of taxing the income of workers takes off, we will all be deeply in the debt of robots as we enjoy greater leisure and enter a new post-industrial renaissance for humanity

That’s many years distant and may turn out to be an unachievable goal but, when delivery drivers are replaced by autonomous vehicles, there will be even fewer humans in the retail value chain, enhancing its’ resilience and reducing the likelihood of mistakes. In fact, machines that are properly maintained and supported won’t make mistakes – that will be left to humans like me who ruin their retail experiences by forgetting to order everything they need.

George Malim


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Internet of Things: The Protocols Landscape

The next era of computing is the Internet of Things (IoT), also known as the Internet of Objects. IoT refers to the networked interconnection of everyday objects, which are equipped with ubiquitous intelligence. A recent report by McKinsey Global Institute reported that the number of connected machines has increased by 300 per cent over the last few years. By 2025, economic impact of the IoT is estimated to range from $ 2.7 trillion to $ 6.2 trillion. Wikibon predicts that the value created from the Internet will be about $ 1279 billion in 2020, growing annually at a rate of 14 per cent.

The International Telecommunication Union (ITU) defines the IoT as, “A global infrastructure for the information society, enabling advanced services by interconnecting (physical and virtual) things based on existing and evolving interoperable information and communication technologies.”

The scope of the IoT is increasing in diverse ways, as IoT-based solutions are extending to virtually all areas of everyday life, from smart homes to smart industrial production. And the evolution of Industry 4.0 has begun.

IoT layered architecture

Fig. 1: IoT layered architecture

The term ‘Internet of Things’consists of two words: Internet and things. The latter refers to various IoT devices with unique identities, which are capable of remote sensing, actuating and live monitoring of certain kind of data. IoT devices are also enabled for live exchange of data with other connected devices and applications, either directly or indirectly, or collecting data from other devices, processing it and sending it to various servers. The other term‘Internet’ is defined as a global communication network connecting trillions of computers across the planet, enabling information sharing.

IoT architecture

As the IoT is capable of connecting billions of heterogeneous objects via the Internet, there is an emerging requirement for a dynamic layered architecture. Fig. 1 represents a standard IoT layered architecture.

Objects layer

The first layer (perception layer) represents physical sensors of the IoT, which sense, collect and process information.

Object abstraction layer

This layer transfers the data acquired by the object layer to the service management layer via secure channels. Data can be transferred using different technologies like 3G, 4G, GSM, UMTS, Wi-Fi, Bluetooth and ZigBee.

Service management layer

This layer enables IoT application programmers to work with heterogeneous objects, irrespective of the hardware platform.

Application layer

This layer enables high-quality smart services to fetch what the customers need. It covers smart homes, smart production units, transportation, smart healthcare-based biosensor equipment, etc.

Business layer

This layer manages the overall IoT system’s activities and services. It is responsible for building the business model, graphs and flowcharts on the basis of data acquired at the application layer.

IoT protocols

Institute of Electrical and Electronics Engineers (IEEE) and European Telecommunications Standards Institute (ETSI) have defined some of the most important protocols for the IoT. These are listed below.

Constrained Application Protocol (CoAP)

Created by the IETF Constrained RESTful Environments (CoRE) working group, CoAP is an Internet application protocol for constrained devices. It is designed for use between devices on the same constrained network, between devices and general nodes on the Internet, and between devices on different constrained networks—both joined on the Internet. This protocol is especially designed for IoT systems based on HTTP protocols. CoAP makes use of the UDP protocol for lightweight implementation. It also makes use of RESTful architecture, which is very similar to the HTTP protocol. It is used within mobiles and social-network-based applications and eliminates ambiguity by using the HTTP get, post, put and delete methods. Apart from communicating IoT data, CoAP allows secure exchange of messages by using datagram transport layer security (DTLS) protocol.

How CoAP works

Fig. 2: How CoAP works

MQTT protocol

Message queue telemetry transport (MQTT), a messaging protocol, was developed by Andy Stanford-Clark of IBM and Arlen Nipper of Arcom in 1999. It is mostly used for remote monitoring in the IoT. Its primary task is to acquire data from many devices and transport it to the IT infrastructure. MQTT connects devices and networks with applications and middleware. A hub-and-spoke architecture is natural for MQTT. All the devices connect to data concentrator servers like IBM’s new MessageSight appliance. MQTT protocols work on top of TCP to provide simple and reliable data streams.

MQTT protocol consists of three main components: subscriber, publisher and broker. The publisher generates the data and transmits the information to subscribers through the broker. The broker ensures security by cross-checking the authorisation of publishers and subscribers.

MQTT protocol is the preferred option for IoT-based devices, and is able to provide efficient information-routing functions to small, cheap, low-memory and power-consuming devices in vulnerable and low-bandwidth networks.

MQTT protocol architecture

Fig. 3: MQTT protocol architecture

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Sequans’ Monarch Platform Delivers VoLTE on Verizon’s LTE Cat M1 Network

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Sequans' Monarch Platform Delivers VoLTE on Verizon's LTE Cat M1 Network

LTE for IoT chipmaker Sequans Communications S.A. has successfully demonstrated the VoLTE (voice over LTE) capabilities of its Monarch LTE Platform live on Verizon’s LTE Cat M1 network.

There are many M2M and IoT applications in a wide variety of market sectors that can benefit from voice capability, including security and alarm systems for home and business, health monitoring wearables, automatic teller machines, retail kiosks, package drop-off stations, fitness bands, in-car emergency applications, people trackers, call boxes for elevators and roadside assistance, parking kiosks, and vending machines.

Georges Karam, Sequans CEO, said:

“VoLTE is needed for many LTE for IoT applications and this successful test of VoLTE on Verizon shows how the market reach of Verizon’s LTE-M network can be extended to include many more applications.”

“Alarm systems, health wearables, and even feature phones that will run on 4G-only networks will all benefit from VoLTE capability.”

Monarch is Sequans’ LTE Cat M1/NB1 Platform, compliant with the 3GPP Release 13 LTE Advanced Pro standard. The VoLTE capabilities of Sequans’ Monarch LTE Cat M1 Platform are enabled by a fully integrated on-chip IMS stack. The platform supports LTE quality of service for fast call setup and low-latency voice calls. Monarch also supports advanced calling features and several major voice codecs.

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