Today, utilities and many other industries use drones extensively to conduct surveys, map assets and monitor business operations. They use drones for tasks as simple as aerial photography or as complex as sophisticated data collection and processing. The global commercial drone market is projected to grow from USD 8.15 billion in 2022 to USD 47.38 billion by 2029, at a CAGR of 28.58% in the forecast period.

Different drone requirements require different investments such as commercial drone pilots with specialized continuous training, cutting-edge software and equipment that supports technical payloads (such as LiDAR, thermal cameras and more). The complexity of the task determines the cost and availability of functions, as well as how data is processed and integrated.

Capgemini and IBM collaborate to drive the future of drone potential

Capgemini’s Energy and Utilities Industry Platform, in collaboration with IBM Ecosystem Engineering GSI Lab, has developed Drone-as-a-Service (DaaS).

Drone-as-a-Service (DaaS), is a Software as a Service (SaaS)-based offering that is hardware independent and fully scalable. It promises end-to-end solutions to manage and monitor a fleet of drones, runs inspection missions to capture high-quality data, accesses inspection reports and derives actionable information through AI-driven analytics—all through a single platform.

DaaS is an intelligent, cloud-based, multi-tenant offering for data processing, data storage and data analysis. It can offer data on demand to different business units within an organization, with the help of various sensors and payloads. The services are activated through access management for data collection, analysis and event monitoring in existing drones which are managed by clients and businesses.

Additionally, DaaS has the potential to leverage smart technologies such as IoT, sensors, 5G, edge analytics and machine learning to improve the monitoring and visualization of assets operations. The flexibility of DaaS in offering a multiplicity of data collection services for different industry use cases makes it unique. For example, for switchyard inspection, a drone would carry thermal imaging cameras, while for an overhead asset survey and inspection, appropriate LiDAR sensors would be used to capture data.

Capgemini reinforces our partnership with IBM Ecosystem with the introduction of a futuristic and sustainable offering that is poised to revolutionize asset management. With our innovative drone-based predictive maintenance solution, we are transforming asset management to the next level.

Contact our Partner Capgemini

Building with IBM

The DaaS offering uses IBM’s Maximo Application Suite (MAS) and Cloud Pak for Data (CP4D) using Industry 4.0 standards. IBM functions as a catalyst in Capgemini’s mission to chart a technologically sound and futuristic course for its global clients.

DaaS uses MAS and CP4D, which have the capability to store, organize and analyze data in the following ways:

Maximo Application Suite (MAS)

Maximo Application Suite is an asset management solution that manages the entire lifecycle of assets. EAM solutions are gaining adoption as enterprises look for technology-driven solutions that can reduce downtime and maintenance cost, increase asset durability and enhance overall efficiency. The data captured by the sensors and housed in the cloud flow into real-time monitoring for 24/7 visibility into your assets, enabling the Predictive Failure Model. DaaS leverages IBM® Maximo® Visual Inspection and puts the power of AI computer vision into the hands of subject matter experts. DaaS uses built-in deep learning models that learn by analyzing images and video streams for classification. Using object anomaly detection, the system dramatically improves production quality and speed. Visual analytics models can also predict a product’s final quality based on current levels of quality.

Industry use case: A fully functional digital twin is the result of MAS in action. It is a digital representation of your entire system and processes. Digital twins allow you to effectively model operations, monitor every aspect of your operation and optimize the output of your system. Digital twins also enable better information sharing between parties—minimizing downtime and creating effective communication between asset OEMs, owners, operators and maintainers.

Data Fabric

DaaS is built on CP4D that, together with Data Fabric, allows Data Virtualization which procures data from surround systems (such as data warehouses) and generates insights on the fly. Intelligent chatbots powered by Watson® Assistant can dynamically and positively alter the business experience. Knowledge catalogues can help organize data effectively, and the data refinery provides out-of-box models for data cleansing. Watson® Discovery in CP4D can help ingest unstructured data (such as inspection reports, progress reports and OEM documentation) and prescribe appropriate SOPs to improve overall asset handling. MVI and CP4D together empower DaaS by providing an edge in visual inspection and foreseeing challenges.

Industry use case: DaaS integrates with IBM’s Health Safety and Environment (HSE) Teams that can build and deploy ML models to analyze and digitize work images and verify compliance by ensuring adherence to the work permits issued (cold or hot work). These ML models can also identify the adherence of the workforce deployed (number of workers approved versus actual deployed) and the overall work hygiene at the site. Additionally, they can monitor vehicle movement and parking in specific zones and generate alerts of vehicles trespassing in no-go areas.

This joint offering testifies to the strength of Capgemini’s partnership with IBM. DaaS has a multi-fold potential to increase efficiencies across industries which are futuristically dependent on drones. In a nutshell, DaaS provides simplified asset and value optimization.

Learn more about the MAS platform

DaaS and beyond

DaaS can be considered for deployment under different scenarios to improve asset surveillance, operational efficiency, industrial safety, environment and compliance. A single multitenant SaaS solution can be used by the renewable industry for multiple jobs such as initial site selection, potential solar and wind energy assessments, topographical and strategic surveys of solar and wind farms, and aerial monitoring of solar and wind assets. In the mining industry, different activities related to health, safety and environment (along with hazards in mines) can be captured and analyzed by different models using the DaaS application. In the oil and gas industry, various activities such as monitoring stack emissions, checking the spread of air-borne pollutants, maintaining assets (to detect leakage, damage or risks) and ensuring safety can be performed using a single DaaS solution.

The advantage of using DaaS is that industry professionals can focus on their core operations, and the service can be customized (while data collection and monitoring can be outsourced based on specific data capture requirements).

Most importantly, DaaS aims to remove the need for the industry to invest its own money in multiple drone hardware and application developments, pilot training and clearances.

DaaS is easy to scale and substantially cuts development costs and time. There is no specific installation or configuration needed based on the activity being performed. The access rights to the DaaS application can be managed as per set policies (which ensures security and enables smart data processing and seamless integration with on-prem/cloud enterprise applications without the need of customization).

About the project team

The IBM EEGSI Lab is a team of technical architects that assists large partners (GSIs) in adopting IBM technology. Capgemini’s Energy & Utilities Industry Platform is the global industry hub and Centre of Excellence (CoE) for Energy and Utilities. Their goal to become the leading strategic partner of the Energy and Utilities transformation, focusing on the energy transition, low carbon tech revolution and changing customer behavior, all while leveraging the power of Intelligent Industry. Together, IBM and Capgemini are ready to create plays, assets and collaterals to engage with potential clients.

Contact your IBM representative and learn how to showcase successful Proof of Value (PoV) to clients
Was this article helpful?
YesNo

More from

AI in commerce: Essential use cases for B2B and B2C

9 min read - Four AI in commerce use cases are already transforming the customer journey: modernization and business model expansion; dynamic product experience management (PXM); order intelligence; and payments and security.  By implementing effective solutions for AI in commerce, brands can create seamless, personalized buying experiences that increase customer loyalty, customer engagement, retention and share of wallet across B2B and B2C channels.  Poorly run implementations of traditional or generative AI in commerce—such as models trained on inadequate or inappropriate data—lead to bad experiences…

A new era in BI: Overcoming low adoption to make smart decisions accessible for all

5 min read - Organizations today are both empowered and overwhelmed by data. This paradox lies at the heart of modern business strategy: while there's an unprecedented amount of data available, unlocking actionable insights requires more than access to numbers. The push to enhance productivity, use resources wisely, and boost sustainability through data-driven decision-making is stronger than ever. Yet, the low adoption rates of business intelligence (BI) tools present a significant hurdle. According to Gartner, although the number of employees that use analytics and…

Achieving cloud excellence and efficiency with cloud maturity models

6 min read - Business leaders worldwide are asking their teams the same question: “Are we using the cloud effectively?” This quandary often comes with an accompanying worry: “Are we spending too much money on cloud computing?” Given the statistics—82% of surveyed respondents in a 2023 Statista study cited managing cloud spend as a significant challenge—it’s a legitimate concern. Concerns around security, governance and lack of resources and expertise also top the list of respondents’ concerns. Cloud maturity models are a useful tool for…

IBM Newsletters

Get our newsletters and topic updates that deliver the latest thought leadership and insights on emerging trends.
Subscribe now More newsletters