Accelerating the Industrial Internet of Things
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Use Cases Autonomous Transport Systems

Autonomous Transport Systems

Autonomous transport systems provide unmanned, autonomous transfer of equipment, baggage, people, information or resources from point-to-point with minimal intervention. They can include the full range of transport vehicles, including trucks, buses, trains, metros, ships, and airplanes. They are most commonly deployed in controlled industries zones but are expected to soon be deployed in public areas with varying degrees of autonomy. 

We differentiate autonomous transport systems from autonomous vehicles. Whereas autonomous vehicles serve individual passengers (who may or may not own the vehicle), autonomous transport systems are interconnected fleets of vehicles owned by a business to service a particular need systematically. 

When discussing autonomous transport systems, the focus is on the interaction among vehicles in a sophisticated system that interfaces with ERP, MES, and other enterprise data management systems. The autonomy of the vehicle is one component of a larger interconnected system of autonomous and semi-autonomous activity with the objective of achieving business or organizational objectives, such as delivering the mail or moving soil from a mine to a processing facility.


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Connected Transportation: A Smarter Brain for Your Train with Intel
Connected Transportation: A Smarter Brain for Your Train with Intel
A modern locomotive, for example, has as many as 200 sensors generating more than a billion data points per second. Vibration sensors surround critical components, video cameras scan the track and cab, while other sensors monitor RPM, power, temperature, the fuel mix, exhaust characteristics, and more.Most of today’s locomotives lack sufficient on-board processing power to make full use of all this data. To make matters worse, the data from different subsystems, such as the brakes, fuel system, and engine, remain separate, stored in isolated “boxes” that prevent unified analysis. The data is available, but the technology needed to process it in the most effective manner is not. As new sensors are added to the machine, the problem escalates.
IoT Based Asset Tracking System
IoT Based Asset Tracking System
The existing system used by the customer could only track a few thousand assets and was able to generate only a few standard set of reports. As the number of assets tracked grew exponentially, the system started to break at the seams. The Tracking devices were from different manufacturers following different protocols. There was no proper integration among the devices to send instant alerts. There are thousands of tracking devices spread across multiple geographies, that are moving. The configuration and troubleshooting of these devices incurred heavy costs, which was a logistics challenge. The existing system did not provide sophisticated Analytics, Business Intelligence and Insights from the data
Escrypt | V2X: Hybrid Communication, Homogeneous IT Security
Escrypt | V2X: Hybrid Communication, Homogeneous IT Security
Mobility promises us a future of connected driving: an increase in driving safety and road safety, autonomous driving, better traffic flow, less harm to the environment, and enhanced public and goods transportation.  However, this future is one, from a technical standpoint, very hard to realize.  The current transmission of data between vehicles is, currently, not fast enough to ensure safety amoungst autonomous vehicles.

The semi-autonomous truck market is estimated to be 260,000 units in 2018 and is projected to reach 1,130,000 units by 2025, at a CAGR of 23.38%.

The autonomous truck market is estimated to be 15,000 units in 2025 and is projected to reach 81.8 thousand units by 2030, at a CAGR of 39.96%.

Source: Businesswire

The autonomous train market, in terms of volume, is projected to grow at a CAGR of 4.87% from 2018 to 2030. The market is estimated at 54,558 Units in 2017 and is projected to reach 106,290 Units by 2030. In this study, 2017 has been considered the base year, and 2018–2030 is the forecast period, for estimating the market size of the market.

Source: Markets & Markets


What is the business value of this IoT use case and how is it measured?
Your Answer

Where are autonomous transport systems used?

The first stage of development testing for autonomous transport systems is in controlled industrial environments such as mines and ports. These areas have well-defined paths and limited variability in the types of obstacles that a vehicle must navigate around. Control of the environment by a single corporation also means that many vehicles are connected to the same system. This increases the ability of a vehicle to foresee potential obstacles and to coordinate action with other vehicles in the system.

Autonomous trains, subways, ships, and airplanes are also being experimented with. Autonomous trains and subways are commonly used today and are significantly easier to manage due to the high degree of system control. Ships and airplanes can and do run autonomously for long durations but are typically not operated without a human operator at the controls. We are moving into a period where the presence of human operators will likely remain primarily to mitigate legal risk rather than with the anticipation that humans will be superior at piloting the vehicle in most circumstances. 

Systems for general road use are being developed rapidly. Highways are widely expected to be the first public roads to see significant autonomous traffic. As opposed to urban roads, highways typically offer a wide field of vision and relatively homogenous behavior among other objects of the road. Urban roads must contend with broken tree limbs, children playing, bikes running stop signs, people pulling out of driveways, and other unpredictable factors. 


Which technologies are used in a system and what are the critical technology?
Your Answer

How are autonomous transport systems connected to information systems?

Data distribution service (DDS) is an industry standard for autonomous vehicles because it is open standard and cross-vendor.


What business, integration, or regulatory challenges could impact deployment?
Your Answer

What are the technical challenges facing autonomous transport systems?

Technical challenges related to autonomy include ensuring reliable data ingestion, guaranteeing real-time response in complex situations, managing complex data flows between vehicles and connected systems, integrating systems, and securing system access to prevent the hacking of vehicles or systems.


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