Level 5 Autonomous Driving Challenges

The challenges of Level 5 Autonomous Driving

Autonomous Driving is classified according to the amount of human driver intervention and ranges from Level 0 (no automation) up to Level 5 (full automation).

Enabling Level 5 Autonomous Driving in Automotive, Defense and other Industries requires collecting, storing and processing data at an unprecedented degree, which has been until now unattainable by Embedded Devices and Edge Computers.

Companies in the Automotive industry are spending billions of dollars in investments for developing Level 5 Autonomous Driving technologies. All these players are encountering a number of new challenges that span across many disciplines and technologies.

Performance

Sensors, LIDARS and other technologies supporting autonomous driving generate unprecedented amounts of data that require ultra-high computational performance that goes beyond the traditional embedded computer capabilities.

Some sophisticated sensors require a bandwidth of 40Gb/s to transfer data, not only in peak conditions, but for continuous operations. Moreover, Level 5 Autonomous Driving applications require constant, reliable and real-time operations while keeping latency as low as possible.

Storage capacity

Level 5 Autonomous Driving applications largely exceed the storage capacity of typical embedded computing devices. Thinking about the 40Gb/s bandwidth mentioned above, it translates to almost 20TB in only an hour of operations.

Ruggedness

High Performance Embedded Computing (HPEC) systems and data loggers installed on vehicles must provide reliable, continuous operations for long period of time in very harsh environment, withstanding shocks, vibrations, dusty environments and wide temperature ranges.

DynaCOR 40-34 High Performance Embedded Computing system for Level 5 Autonomous Driving

Certifications

Embedded and electronic systems and Edge Computers installed into vehicles must comply with industry standards.

Automotive certifications, such as E-Mark and IEC 60068-2-6 / 60068-2-27 for shock and vibration are objective ways for characterizing the behavior of the system under stress in actual operating conditions.

Compactness

Space is more than often at a premium in embedded applications. Systems designed to fit into embedded environments must come with compact size, to be easily installed into vehicles.

However, HPEC systems provide tremendous amount of computational power and they easily heat up: dissipating such an intense heat would require a proper and powerful cooling system that can be easily installed in the vehicle.

Cooling

High Performance Computing systems are typically bulkier than embedded systems due to heat dissipation issues: they are usually equipped with big fans that cannot be used in embedded applications where performance is sacrificed to adapt to space constraints.

However, High Performance Embedded Computing systems for Autonomous Driving must provide HPC performances into a vehicle.

Eurotech has a lot of expertise in designing liquid-cooled HPC (High Performance Computing) and HPEC systems. Liquid cooling is an ideal solution for HPEC systems in Autonomous Driving, as most of the cars are already equipped with liquid cooling systems.

Compared to air cooling, liquid cooling allows more computational density and a better energy efficiency: even though Eurotech’s HPEC systems can use up to 500W, the coolant would maintain a temperature of around 41-43°C.

 

The DynaCOR 40-34 and the DynaCOR 50-35 are unique examples of High Performance Embedded Computing systems that comply with all these requirements, winning the challenges of Level 5 Autonomous Driving: they provide flexible and configurable platforms that allow the creation of in-vehicle Data Centers.

3 key railway standards with which every on-board embedded and IoT system should comply

Railway companies looking for new on-board electronic equipment or intelligent transportation systems should consider products that follow specific requirements in terms of operating temperature, shock and vibration resistance, EMC, and so on, in order to guarantee consistent and reliable performance in harsh and contaminated environments such as trains.

That is why on-board electronic devices like IoT gateways, edge computers and intelligent transportation systems should comply with the parameters defined by specific railway certifications. We will discuss three key standard requirements to meet the needs of today’s on-board railway and rolling stock applications..

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How can people counting make events run smoothly?

Whether it’s venue, catering, speakers, delegates or topics, many factors have to come together in just the right way to create a truly successful conference or exhibition. Weeks, or even months, of planning go into ensuring every detail of even the smallest event is the best it can be. So, once we have everything in place and the conference is underway, how do we know that what we’re doing is working and how can we tell which areas of a show are the most engaging?

We can ask people for their feedback and send post-event surveys all we like but nothing beats hard data that tells us, in real time, what we need to know.

At Red Hat Summit 2015 in Boston, one of the biggest open source technology events in the world, we saw just how easily this issue of event analysis can be addressed.

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Does your enterprise depend on the Mobile Edge? Considerations for mobile computing at the edge of fleet enterprises

In the United States alone there are over 26 million commercial vehicles on the roadways and in operations1, ranging across the spectrum of logistics and heavy moving equipment to agriculture equipment and waste management vehicles.  In today’s connected enterprises, these commercial fleets are managed through tightly integrated operational systems that perform a multitude of services, including fleet management (automatic vehicle location, asset tracking, route optimization), monitoring of vehicle health and diagnostics, vehicle operator console operations, electronic data recording, and video capture.  These systems improve operational efficiencies, reduce costs, and enable delivery of enhanced services.

Enabling technology for all of these applications is the “Mobile Edge”, the ability to extend an enterprise’s operational systems to mobile computing platforms on deployed fleet vehicles.  A variety of options present themselves to both operators deploying these systems and technology companies offering communications solutions to those operators.  In choosing the right solution for the Mobile Edge, the operator or integrator must consider both hardware and software aspects of their system requirements.

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How do you take your coffee? – asked the vending machine

Imagine how many times that expression is heard every day.  It likely conjures up images of a Swish Viennese Cafè but the truth is vending machine technology has advanced significantly to include coffee and a myriad of other snack options.  In the U.S. alone the vending machine business is a $7 billion industry with more than 5 million machines and forecasters suggest by the end of the year there will be more than 53 million machines globally.

The same machine that dispenses coffee can dispense soft drinks, water, candy bars, chips and other snacks.  In the past the items vending machines actually did dispense was hit and miss based on what was actually available, if you had the right coins and if they were actually accepted by the tin box in front of you.  In those distant days you probably thought – who on earth manages these vending machines, why don’t they ever work, why don’t they have what I want and when is the service technician coming?

Eurotech_Icon - Vending_Machines_Man
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Smart Fridge

With headline like these:

Tesco stores throw out food after fridges fail

Families fill car boots and suitcases with food thrown out by Tesco after supermarket fridges break down in the heat

is it not time that organisations with existing base of refrigeration assets turned to the Internet of Things to put in place retro fitted sensors to monitor the performance and key indicators on. Identifying potential problems early can help to reduce failure rates and save on energy, food waste and potentially damaging headlines.

With Everyware Cloud – the M2M / IoT Integration Platform –  and Intelligent Edge Gateways Eurotech can help customers connect and monitor any type of asset.

The IoT cloud connectivity for existing refrigeration assets let organizations to monitor in real-time parameters like:Eurotech_Icon - Refrigerator_Connected

  • Power consumption
  • Inside and outside temperature and humidity
  • Motor vibration
  • Door open / close
  • Leakage detection
  • Refrigerant pressure
  • Compressor vibration

Knowing the assets’ status, the organizations can quickly react to prevent a failure or minimizing its consequences.

 

Simplifying Complex M2M/IoT Systems with the Multi-Service Gateway Approach

While many M2M/IoT systems are complex, an environmental monitoring system provides an excellent example for the various sensors and devices that must be combined to create a cohesive M2M/IoT system.  Consider a cloud connected environmental monitoring system with high precision air pollution sensors and real time data access.  The system must be rugged and compact to withstand the elements and designed to monitor traffic, industrial, construction and urban areas for temperature, gaseous pollutants, particulates, electromagnetic fields, radioactivity, and sound pollution.   To add another layer of complexity, the system must be built to seamlessly connect to the cloud and send data from the field to the business application in real time.

The M2M/IoT marketplace is full of hundreds of piecemeal technologies that can be cobbled together from different vendors to form a solution, but the environmental monitoring system is best developed using the Multi-Service Gateway approach (Figure 1).

M2M_IoT_gateway_scheme

Figure 1: Multi-Service Gateways consolidate multiple businessrelevant tasks.

 

A Multi-Service Gateway is ideally suited for the environmental monitoring system to connect sensors, actuators, and meters to the business enterprise. It enables bidirectional communication between the field and the cloud and offers local processing and storage capabilities to provide offline services and near real time management and control of the devices in the field.

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IT-Centric IoT Device Management

The edge of the IoT is where solutions connect, communicate and interact using sensors, actuators, gateways, agents and controllers. As technology advances vendors are touting “advanced management capabilities” for these devices at the edge. These capabilities vary, ranging from the simple ability to turn a device on and off to more complex actions such as updating software, managing Wifi connections, configuring security policies or changing data parameters.esf_framework

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The Benefits of a Java-Based Application Framework for IoT Projects

IoT projects present many challenges, even when the hardware is designed exactly to customer specifications. Building on proven architecture and software building blocks that would require many years to develop, the use of a Java-based IoT application framework will result in shorter, more deterministic device software development. Using an IT-centric approach to implement the device logic in smart edge devices improves both device management and embedded application management. Once this standard software platform is in place, connecting and getting business relevant data to the cloud is simpler than it ever has been before.

An advanced software framework that leverages OSGi and Java both isolates the developer from the complexity of the hardware and communications infrastructure and also complements the Multi-Service Gateway hardware for an integrated hardware and software solution.

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The benefits of IT-centric application development to implement business logic in smart edge devices/service gateways are:

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agriculture wine plants

The Internet of Things: how IoT helps producing high quality wine

It’s easy to slip into the habit of thinking of the Internet of Things as a highly technical, industrial tool at home in factories, or fleets of high powered vehicles, but who’d have thought it can also help plants grow?

It can be near impossible to predict what any one growing season will bring. So much is at the mercy of the weather, availability or certification of crop protection products and numerous other factors which have to be given a ‘best guess’ in order to plan for them. The best way to predict the most likely outcome in any season is, of course, experience.

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