Commercial autonomous drone advancement

Since Amazon announced the testing of drone deliveries nearly a decade ago, commercial drones have continued their flight across a variety of industries. Organizations around the world deploy commercial drones for deliveries or to gather video or images with an onboard camera. Drone inspections are already popular in several industries, but commercial drone usage received a boost with the recent announcement that the UK is set to become the world’s largest automated drone superhighway in two years.

What are autonomous drones?

The European Union Aviation Safety Agency defines an autonomous drone as “able to conduct a safe flight without the intervention of a pilot […] with the help of artificial intelligence, enabling it to cope with all kinds of unforeseen and unpredictable emergency situations.”

Read More: C1000-059: IBM AI Enterprise Workflow V1 Data Science Specialist

If drones can use artificial intelligence (AI) to determine when to take off, which direction to fly, how to deal with external factors and how to return once the mission is over, there will be less need for pilots or drone operators.

Why are unmanned air system traffic management and “beyond visual line of sight” critical to the future of commercial drones?

Many countries are drawing up regulatory frameworks for low-altitude traffic management to accommodate the future of drones. This framework will cover roles, responsibilities and protocols to share data as part of drone operations. In the U.S., federal agencies are creating Unmanned Aircraft System Traffic Management (UTM). In the UK, the Civil Aviation Authority (CAA) is working toward something similar.

Just like road vehicles, identification of a drone is one part of the requirement for UTM, and the FAA in the US already requires all drones to be identified. There are also plans to include Remote ID for drones that will provide identification and location information that others can obtain.

In the U.S., a drone operator is legally required to have visual line of sight (LOS) to the drone. To enable large-scale commercial drone usage like the UK’s superhighway, the regulatory framework needs to allow for “beyond visual line of sight” (BVLOS) piloting.  Some countries with large amounts of remote locations, such as Iceland, Norway and Sweden, have already enabled BVLOS as means of supporting isolated communities.

How can drone-in-a-box help?

Frost & Sullivan defined drone-in-a-box in a 2018 report on drone delivery: “Sensor, communications, hardware and software technologies have advanced to the point that innovative companies can offer semi- or fully autonomous vehicles that can be automatically launched and recovered to base stations or enclosures. These solutions are often referred to as ‘drone-in-a-box’ because structures are required to recharge, protect, or recharge and protect drones between mission legs or between different missions.”

Today many companies invest in drone-in-a-box as a mainstream component of future industrial drone operations. At least two other features will become part of this component as 5G becomes the connectivity infrastructure:

1. Transfer of the drone imagery from the base station to the processing organization to enable near real-time decision making.

2. Support for edge computing, so the drone can be directed based on what it sees during an inspection.

What supports will maximize benefits from commercial drone inspections?

When adopting drone monitoring technology into an enterprise, it is vital to create a plan that maximizes efficiency. By combining drone-captured images and videos with these seven technologies, enterprises can automate workflows and improve the productivity of their business operations.

1. Storage for imagery

Drones capture high-resolution videos of the infrastructure or asset that needs to be monitored during a drone inspection. In general, a 4K-resolution video taken at 30 frames per second needs about 760 MB of storage for every minute recorded. Recording drone footage for even just a few days can add up to terabytes of storage. Therefore, enterprises have realized cloud storage is a cost-effective way to store and back up footage for later analysis.

2. Image stitching

Stitching videos or images together allows companies to see the full structure of an asset rather than spending time and money to monitor footage for changes. This is particularly useful in large structures like bridges or construction sites. This efficient tool helps managers identify issues and observe the pace and progress of solutions.

3. Other relevant datasets to support analytics

Initially, analytics may simply compare the change in the asset over time. When additional aspects of data are included, planners can achieve richer interpretation, analysis and pattern discovery. For instance, when data on the rate of rusting, types of rust, types of structural damage from rust and types of weather patterns are used with drone images of a bridge, it assists in predicting areas of potential structural damage versus superficial changes.

Urban planners can quickly complete planning activities when existing data of nearby topography, buildings, roads and infrastructure are used along with drone images of a particular area. Similarly, the use of weather data such as temperature, wind direction, potential for rain and past data of wildfires may help experts monitor and identify a change more quickly than with just the drone images.

4. Finding patterns with people

A bridge inspector who has spent 20 years on the job is able to look at a particular crack or concrete spalling and immediately tell if it is a cause of concern or not. The expert inspector considers depth, color, location and other factors to make this assessment. Human expertise and knowledge help identify patterns to create relevant datasets that can train computers.

5. Computer vision

Computer vision trains AI to identify the same patterns an expert inspector would see. For example, by training computers to identify imagery of a variety of concrete spalling, AI can automatically monitor images of the bridge to locate defects. This complementary drone solution eliminates the need for people to go through hundreds of hours of drone footage.

6. Rules and decision making

Once people identify a set of patterns in the imagery and teach AI to do the same, organizations can set up business rules. For example, if a particular type of structural defect is found on the roof of a house, run the drone inspection again in x months to see if there is a change. In a more critical scenario, such as if the construction blueprint and actuals are out of sync, a variety of departments will be prompted to act immediately.

7. Digital twins

Drone mapping of a building or set of structures, such as a telecommunication tower, can help create a digital twin. This digital twin can then help companies understand how the physical asset is functioning based on real data. For instance, with a digital twin, organizations can study and predict the ways a hurricane could impact the position of mobile antennas on a telecommunication tower. These predictions can inform engineers of individual towers that will need maintenance in advance of such an event. Moving from reactive to predictive maintenance can save organizations from downtime and support greater efficiencies of business operations.

Evaluating drone use in your organization

Automate inspections and reducing manual effort with drones will drive significant growth in the coming years. The global drone services market is projected to grow from USD 9.56 billion in 2021 to USD 134.89 billion by 2028 at a CAGR of 45.9% in forecast period 2021-2028. As this market grows, these industries will demand more specialized drone services.

Source: ibm.com

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IBM Engineering Workflow Management is the tool of choice for the IBM zHW team

Imagine a digital engineering workplace where thousands of people are building a single system. This system is used by two-thirds of the Fortune 100, 45 of the world’s top 50 banks, 8 of the top 10 insurers, 7 of the top 10 global retailers and 8 out of the top 10 telcos as a highly secured platform for running their most mission-critical workloads. The development effort involves coordinating manufacturing, chip design, hardware, firmware, testing and defect tracking, while also meeting stringent regulatory requirements across a variety of industries and governmental standards.

This is the challenge that teams working on IBM Z® (the family name for IBM’s z/Architecture mainframe computers) face with every new product release.

Looking to the future

The IBM Z developers embarked on an extensive year-long evaluation of the development tools available in the marketplace that would help them manage their daunting engineering workflow. To carry out this evaluation, stakeholders created a matrix chart showing which solutions included the required integration capabilities for the tools used by the team.

The team selected components of the IBM Engineering Lifecycle Management (ELM) solution, namely IBM Engineering Workflow Management (EWM), a fully integrated software development solution designed for complex product management and engineering, as well as for large, distributed development organizations that produce mission-critical systems subject to regulatory compliance. But this choice was not a foregone conclusion.

“By being completely objective and allowing the criteria and data to do the talking, we were led to EWM,” said Dominic Odescalchi, project executive manager of IBM zHW program management. “EWM was the consensus tool that we collectively agreed upon to provide the best solution.”

The advantage of IBM ELM tools

The zHW platform development team will leverage EWM as the central hub of engineering data, taking advantage of the customization capabilities within the broader ELM solution. This way, every team can adapt the processes that fit them best while remaining coordinated across one view of the development data and progress. Managing this data is critically important given the highly regulated workloads that are run on these systems across a variety of industries, governmental agencies and countries.

Given the holistic design of IBM Engineering Lifecycle Management, the team has also adopted the IBM Engineering Test Management tool to manage the comprehensive verification and validation of the hardware, again leveraging the one view and traceability across development data.

“With EWM’s integrated tool stack, key data will be readily available through connection to various team repositories,” said Odescalchi. “This will enable us to kick the doors wide open to automating and aggregating data. It’s going to free up countless hours to focus on performing higher value activities.”

Source: ibm.com

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Digital engineering is the answer when flawless, accountable production means life or death

Digital technology transformations have streamlined analog processes for decades, making complicated tasks easier, faster, more intuitive and even automatic. The modern car is the perfect expression of this idea. Cars produced in the last few decades are more than cars — they’re a bundle of digital processes with the ability to regulate fuel consumption, detect unsafe conditions, understand when the vehicle is coming close to a collision and ensure the driver doesn’t unknowingly drift out of their lane.

The array of sensors and actuators, cameras, radar, lidar and embedded computer subsystems in these vehicles can’t just be useful gadgets; they must flawlessly ensure the safety of the driver and passengers. These incredibly complex systems are often developed by different engineering teams or companies. Without the proper development processes, bugs can go unnoticed until after the model ships. For car manufacturers, ensuring that their systems are safe is a matter of life and death.

If a car manufacturer finds a flaw in the self-driving system only after the model has shipped, they face a clear crisis. There isn’t time to contact the dealers, to email drivers or to erect billboards warning of the flaw. The issue must be fixed immediately, or the car manufacturer could face irreparable damage. If the computer system was designed with a firm digital engineering foundation, the manufacturer could easily fix the issue by sending out a “cloud burst” to update every car on the network before the flaw becomes dangerous.

Digital product engineering enables complex, high-stakes development

The goal in digital engineering is to not only minimize flaws in every outgoing vehicle, but to establish a development environment to ensure that once a flaw is detected, it can be fixed quickly and safely. To achieve this, we recommend that companies embrace digital product engineering and digital thread technology. A digital thread is an engineering process whereby a product’s development can be digitally traced throughout its lifecycle, upstream or downstream.

Since the invention of digital technology, businesses have been using computers to automate shipping systems, supply systems and warehouse systems. As the power of that technology continues to grow, businesses are applying the same principles of automation to the development process as well.

Businesses can now create an easy-to-access digital repository for collaborators to work on or view. Updates to the product are made within that central source, ensuring everyone has access to the most up-to-date version of the product.

Digital product engineering is an evolving process, a future-state that organizations need to achieve to make the world a safer, more secure place. Digital engineering holds such promise that the US Government Department of Defense has stipulated in their digital engineering strategy that any subcontractors they work with must use digital engineering processes to ensure transparency, safety and accountability for their high-tech defense systems.

At the highest-level, digital engineering is a holistic, data-first approach to the end-to-end design of complex systems. Models and data can be used and shared throughout the development of the product, eschewing older documents-based methods. The goal is to formalize the development and integration of systems, provide a single authoritative source of truth, improve engineering through technological innovation, and establish supporting engineering infrastructure to ease development, collaboration and communication across teams and disciplines.

Digital thread can provide users with a logic path for tracking information throughout the systems’ lifecycle or ecosystem. By pulling on the digital thread, engineering teams can better understand the impact of design changes, as well as manage requirements, design, implementation and verification. This capability is vital for accurately managing regulatory and compliance requirements, reporting development status and responding quickly to product recalls and quality issues. In terms of digital engineering, a digital thread represents a significant role in connecting engineering data to related processes and people. But a digital thread is not plug and play; it’s a process that must be designed from the ground up.

The IBM digital engineering solution

To make it one step easier for your organization, IBM® Engineering Lifecycle Management (ELM) can establish the ideal base for your company to pursue digital engineering transformation. ELM is built from the ground up around the digital thread model. Each lifecycle application seamlessly shares engineering data with every other lifecycle application, such as downstream software, electronics and mechanical domain applications. ELM leverages the highly-proven W3C linked data approach using Open Services for Lifecycle Collaboration (OSLC) adapters for both internal and external information exchange — the same approach used to seamlessly connect web applications across industries.

ELM leverages OSLC to connect data and processes along the engineering lifecycle. By enabling this standards-based integration architecture, engineering teams can avoid the complications inherent in developing and maintaining proprietary point-to-point integrations.

Lumen Freedom, a manufacturer of wireless charging units for electric vehicles, wants to provide an untethered world for electric vehicle owners. In pioneering this innovation, Lumen’s design management became increasingly complex and difficult to manage. To level up their product development goals, Lumen adopted digital engineering lifecycle management tools from ELM that allow them to capture, trace and analyze mechanical, hardware and software requirements throughout the entire product development process. “Given that DOORS® Next and ELM are essentially standards in the automotive industry, we chose IBM for our preferred toolchain,” says David Eliott, Systems Architect at Lumen Freedom.

ELM maintains a linked data foundation for digital engineering and provides data continuity and traceability within integrated processes. With global data configuration, engineering teams can define a consistent baseline and provide central analytics and reporting components. ELM fosters consistency across all data while providing an automated audit trail, ensuring ease of access to digital evidence for regulatory compliance.

Source: ibm.com

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Boosting engineering efficiencies with digital threads

As the demand for agile development grows, so does the demand for digital threads. But what are digital threads, and what is their value?

Digital threads enable a product’s development through its lifecycle domains to be digitally traced. The tracing can be in either direction, upstream or downstream in the product development lifecycle.

“Digital” means that all the paths are electronic — no one is searching through filing cabinets looking for requirements or test documents. “Thread” means there is a traceable path that anyone can follow between processes and across data domains.

The value in digital threads is the ability to quickly trace an entire development process, digitally identifying causalities between the processes and ensuring that their datasets are consistent. When there is a product quality issue, the digital thread allows for the part or subsystem to be traced back through its lifecycle. Original design concept, requirements, test cases, quality checks, and signoffs are all available to the engineering team diagnosing the quality issue. If a requirement needs to be changed, that change’s impact can be determined digitally by its logical thread.

The need for digital thread enablement has been amplified by growing market pressures for development to be more agile, as well as the increasing software integration in “smart products.”

Digital threads in agile development

The need for agility is especially clear when dealing with supply chain issues. Companies need to know the dependencies in product design for every part and subsystem.

This is important for accelerating reaction time, for instance, when a delay from one vendor forces the substitution of another vendor’s part. Leveraging a digital thread helps companies automate changes and execute them faster. Manually managing changes can make an organization subconsciously adverse to change, which is completely averse to the concept of being agile.

Digital threads in software integration

The increasing integration of software introduces a new market model for many companies, and it increases the need to track and maintain their products in market. Software offers an attractive potential revenue stream through in-market upgrades and enhancements. Maintaining a digital thread helps engineering teams automate necessary processes and leverage data analytics for better insights to proposed changes, such as optimizing the release of fix-packs, retro-functions, and incremental enhancements.

The digital thread is incredibly valuable in the development process. It enables decision-makers to analyze the impact of changes before they are made, establish cross-functional KPI’s for measuring readiness and progress, or more readily respond and report on cross-functional compliance requirements.

IBM designed the Engineering Lifecycle Management portfolio on a digital foundation that not only leverages a single view of digital development data, but also leverages an industry-standard, open exchange format of Open Services for Lifecycle Collaboration (OSLC). The IBM Engineering requirements, test, and workflow management tools, as well as the systems/software modeling tool, all leverage this digital foundation to establish traceability across the development environment. This ELM digital foundation can be leveraged via its OSLC architecture by third-party tools and other domain applications, further extending the capabilities of ELM’s digital thread services. This would allow a manufacturing management system to extend the digital thread traceability across development into the actual product’s manufacturing.

Source: ibm.com

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Unlock the power of digital engineering: What complex products developers need to know

The development of increasingly complex products is becoming more challenging. Think about companies in the automotive, medical device or aerospace and defense industries, for example. Not only is it difficult to staff highly technical teams, but increasing compliance and regulatory oversight, additional safety concerns, shrinking product lifecycles, and growing reliance on software for product differentiation add to the complexity.

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Today’s complex product and software development teams also rely on expanding partner and supplier ecosystems. Navigating and allowing for the coexistence of different work cultures, development tools – both old and new, and the competitive mandate to leverage all their data for better decision making, market insight, and product quality, compound the engineering challenge.

Some companies have adopted a holistic approach to their development environment. Tools that encompass requirements, test, and workflow management can provide the process and data foundation to help address many of these factors. But for companies that do not adopt a holistic development solution, at a minimum they need to incorporate an open, industry standard service for exchanging data between logical development processes efficiently.

The industry standard service that we see most companies adopting is Open Services for Lifecycle Collaboration (OSLC). IBM has been a long-standing proponent of OSLC, but we wanted an unbiased view on the state of the market, so we engaged with VDC Research Group, Inc. to publish this whitepaper, OSLC – A Driving Force behind Engineering Process Integration.

VDC’s research and resulting paper highlights the advantages of adopting a standard approach for data and workflow integration across your company’s development processes. With inputs from over 700 engineers and product development professions, their market insights are compelling testament to the power of an integrated development lifecycle environment enabled by OSLC.

The IBM Engineering Lifecycle Management (ELM) solution provides the best of both worlds – a holistic development environment underpinned by OSLC. However, the premise of digital engineering is to introduce efficiencies and agility into even more engineering practices through the use of digital representations and virtual exploration and validation of complex systems. So, IBM ELM also provides tools for model-based systems engineering, process management, reporting, and engineering data analysis.

The realization of digital engineering relies on all these capabilities with the ability to manage the digital thread across all data sets and domain models. Many data sources need to be integrated and orchestrated into a single lifecycle framework that leverages a trusted source of truth. OSLC is currently the only standards-based way to address this challenge, so the IBM ELM solution leverages the OSLC service for exchanging data. And because OSLC is an open standard, IBM ELM establishes an extensible engineering data foundation open to other applications, regardless of domain modeling languages and tools used.

Digital engineering is all about enabling flexible cross-discipline innovation of complex software-driven intensive systems, from conception to delivery. Based on an open architecture that implements OSLC, IBM ELM advances and extends the power of digital engineering to companies and their increasingly vast ecosystems of partners and suppliers who collaborate to bring higher quality products that address stakeholder needs to market faster at lower cost.

Source: ibm.com

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How to simplify and accelerate advanced automobile development

The automotive open system architecture (AUTOSAR) was developed in 2003 by engineers in the automotive industry to create an open and standardized software model for electronic control units (ECUs) used in vehicles. These engineers foresaw a seismic change in automobile engineering. Sophisticated software, control units, computing power, and cloud connectivity would enable the development of increasingly complex cars that integrate driving assist, artificial intelligence, crash avoidance, and eventually full autonomous operation.

As the software critical to automobile development advanced exponentially, the industry needed software standards to enable several aspects of development: reuse and transferability across variants and versions, ecosystem collaboration, compliance with safety requirements, ease of maintainability and serviceability, and design of greener, more sustainable vehicles. Today, compliance with the AUTOSAR standard is part of the motor industry software reliability association’s (MISRA) guidelines for developing embedded control systems and standalone software used in road vehicles.

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For development teams, the shift from a mechanical to a software mindset and skillset to deliver advanced automobiles is challenging. AUTOSAR provides a “common playbook” that automotive OEMs, partners, and suppliers can all leverage to better collaborate and innovate. But the power of AUTOSAR is not without its own level of complexity. The standardized software architecture requires engineers know how to code and follow specific guidelines to reap its full value. Because it is difficult to staff teams of coding experts, existing engineers need to invest significant time to learn and adapt to the architecture. Considering shrinking product lifecycles and the need to bring differentiated products to market faster, time is a luxury companies can ill afford.

For AUTOSAR to truly deliver on its promise to help the automotive industry leverage standardized software, it needs to be as easy to use as possible. IBM Engineering has addressed the challenge of making AUTOSAR easier to use by developing and delivering the IBM Engineering Systems Design Rhapsody – AUTOSAR Extension. Through a graphical but formal design environment, engineers with little formal AUTOSAR knowledge can focus on the software logic. The offering generates AUTOSAR-compliant artifacts, including production code.

The IBM AUTOSAR Extension provides the capability to convert SysML and UML models into AUTOSAR and generate software components for the Classic platform and applications for the Adaptive platform through UML diagrams. It also supports a flexible development process that allows for late re-targeting, to address different design solutions and price points.

As the AUTOSAR specification represented a major step forward in the development of increasingly complex software-driven electronics in automobiles, the IBM AUTOSAR Extension represents the next step along that same journey to substantially improve the development efficiency and quality of software running the car. Companies can bring advanced products to market faster without being experts in the standard.

Source: ibm.com

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