Interview with JoinPad

AREA member JoinPad provides cloud-based and contextually aware software that simplifies processes in a number of industries. The company’s BrainPad product integrates enterprise resource systems and sensor networks to add Augmented Reality visualization and contextual computing to existing business processes.

This month we interview Nicolas Pezzarossa, Global Sales and Business Development Director of JoinPad, about the enterprise use cases his company is encountering for its products and services.

In which industries are you finding the greatest interest for your products and services?

We see strong interest from providers of energy supplies and infrastructure. Oil and gas has the largest proportion of such companies. Besides this, we’re finding companies in other industries getting involved with Augmented Reality:

• Energy
• Automotive
• Manufacturing
• IT hardware, infrastructure and services
• Retail
• Tourism

We’ve also provided solutions for use cases in these industries.

What are the reasons for AR’s popularity in these companies?

We believe it’s due to growing awareness of the value that Augmented Reality brings in conjunction with digital transformation. The ROI of individual AR use cases is becoming evident, and there’s an increasing maturity of hardware platforms for this environment.

We’ve also received much interest in our smart glasses SDK, and as well in our Smart Assistance solution that offers guided assistance as an “augmented operator’s manual” and expert collaboration in real time.

With whom do you partner most often?

We partner with well-consolidated players active in the field of consulting to large industrial companies in IT infrastructure for manufacturing processes, where we can supply the AR-related components in an OEM-type of integration.

Has employee performance in the workplace prior to AR introduction been studied by your customers?

Most of our customers have detailed statistics about performance or time taken to complete specific tasks, and to which we can correlate our solution. In other cases we’ve performed a detailed analysis of their work processes. Our product also contains a module for work order management that enables generation of KPIs for specifically measuring this type of work performance for comparison purposes.

What are common metrics, and do you recommend customers choose their own?

We find that in most cases the most important factor is time to complete a task (for increasing efficiency). But others include the ratio of possible to actual mistakes and the value of avoided damage, as well as the level of fatigue or satisfaction of operators.

As we are discussing the consequences of a disruptive technology, another important factor is the possibility of enabling new work processes. Although this is more difficult to measure, it offers large potential for increasing efficiency.

We always emphasize the importance of evidence for a return on investment in all phases of a project. This is also essential for advocating internally to stakeholders and management for the adoption of AR.

What is your company’s recommended approach to introducing AR in an organization? Are there steps or a model or method you follow?

We take a phased approach and in a preparatory phase offer a workshop for defining possible use cases and analyzing current work processes. We then propose a proof-of-concept phase in which we offer a basic solution with limited functionality. This allows the customer to experience the new solution and see its potential. We subsequently initiate a pilot phase with actual data exchange, followed by a roll-out phase where the application is introduced into actual work processes.

How is data prepared for your customer projects?

All data must be processed to efficiently support the use case. In particular, when connecting to an ERP system it’s important to choose the data sets specifically supporting the use cases.

Do you get involved in the design of the content that will be used in pilot projects?

Normally the customer asks us to provide the content as well as the design of the user interface. In the case of smart glasses this can involve an innovative interaction design. Key to project success is to propose visualizations that help solve the specific problem at hand and improves visual perception.

Our experiences working with customers have allowed us to develop specific templates for smart glasses applications that ensure efficient intake of the relevant information.

What is the profile of the typical person who performs the selected tasks prior to AR, and what are their attitudes?

Augmented Reality, particularly when used with smart glasses, has the major benefit that even untrained operators can perform complex tasks. But also highly trained operators benefit from availability of real time data where it matters.

In most cases operators are satisfied about working with innovative tools that they appreciate as supporting their work tasks. But the impact of new technologies on human resources and work safety must nonetheless be carefully monitored.

Do you study project risks, and do customers perform user studies?

Risk analysis is always part of our use case analysis, just like recommended fallback scenarios.

Although most customers don’t plan user studies themselves, we offer a questionnaire process both before and after a pilot for evaluating improvements for purposes of the roll-out phase.

What are the system components the customer must provide for a successful project?

This is highly dependent on the use case but there is in fact no requirement that customers provide us with system components. However at various times they do provide us with components ranging from full packages of 3D files to databases and API access.

What type of recognition and tracking technologies do you support, and what are the effects of lighting?

We work with all recognition and tracking principles (e.g., image, bar code, natural features, SLAM, depth sensing, etc.), but based on our proprietary core algorithms.

Lighting represents a challenge that in many cases can be overcome, yet it influences tracking stability. It’s always possible to correct this influence using other types of sensors, or to reduce its impact with fallback scenarios.

Do you use IoT, and is AR content locally archived or accessed over a network?

We have specifically developed and deployed an IoT module in our AR platform BrainPad that is used today by one of our customers in the energy industry to retrieve data from sensors on industrial equipment in the field in real time. We thus fully support IoT data integration.

For AR content, there are different scenarios involving both kinds of access and integration, depending on the workflow.

What are the greatest challenges you face in current projects?

One of the largest challenges is in the need to prove ROI on every single use case, which is often complex as many industrial and manufacturing processes are highly intertwined with other processes.

What are the future plans or next steps for JoinPad?

The next steps are to further grow our activity and supply more publishable customer use cases to further support the adoption of the technology in industry. In particular, Joinpad will intensify its education effort to spread knowledge about the value and design of AR applications by conducting workshops offered to technology experts and managers, as well as in academic initiative.