Internet of Things: Setting business vision on speed and agility
Agility is a business vision. Your data platform should be agile so that you can continue to adapt to an ever-changing competitive climate.
The Internet of Things (IoT) offers a core data platform for the 21st century. Agile IoT technology can drive the speed and provide the flexibility to pivot your business response in any necessary direction at a moment’s notice. If you don’t think IoT technology is coming your way any time soon, you might be surprised to learn that IBM is working with partners and customers to embed IBM Watson IoT technology powered by cognitive analytics into products we use daily.
These products include automobiles, clothes dryers, earphones, elevators, self-driving vehicles, wearable devices and even drones for inspecting cell towers. IBM also enables IoT-centric, hyper-local weather forecasting to be built into any application through its deep investment in algorithms, application programming interfaces (APIs), cloud services, data, and the acquisition of The Weather Company in 2016.
Speed and agility of Internet of Things applications
Advanced analytics is the smarts that enable these and other IoT applications to deliver on the promise of business speed and agility. When embedded into your IoT-enabled business infrastructures and consumer-facing offerings, analytics algorithms—cognitive, descriptive, predictive or prescriptive—can deliver continuously optimized and contextualized outcomes 24x7. Among other capabilities, Watson IoT technology can drive the real-time pattern recognition—environmental conditions, faces, gestures, voices and so on—that helps your organization to algorithmically learn from real-time feeds and drive predictive responses with a high degree of confidence. Leveraging these sophisticated technologies, businesses can reinvent themselves and disrupt their industries before their rivals realize how far along they are.
Delivering on this IoT vision demands that CIOs, CDOs and CTOs catalyze a fundamental change in how their organizations develop applications. The IoT-driven applications that truly transform business are expected to be those that are developed with speedy, agile, team-based practices. And, in turn, those practices require that your IoT app development teams—which should include business analysts, data engineers, data scientists and subject matter specialists—share a common, cloud-based collaborative platform. This development environment should be built on a high-performance data lake and span a hybrid architecture that’s equally capable of handling structured and unstructured data. It needs to also support agile building, testing, refinement and deployment of analytics algorithms into myriad IoT deployment roles, both at the edges and in the cloud.
Internet of Things app development best practices
Primary IoT application development best practices can provide the necessary speed and agility today's businesses require:
- Tap into the cognitive IoT APIs on the IBM Bluemix development platform to make putting these capabilities into programs easier for developers
- Embed algorithmic intelligence directly into IoT-enabled devices and apps, so that these endpoints can adapt continuously and react locally to their environments and, as needed, to metrics and commands from neighboring devices
- Rapidly access, configure and tweak any analytics algorithm—including those discovered on the fly in neighboring nodes—that is suited to the challenges of IoT data analytics
- Optimize analytics algorithms on any size device at the edge or at gateways in containers on widely supported processing frameworks, including Apache Hadoop and Apache Spark within a distributed IoT fabric
- Build in-memory IoT models that analyze data as it streams at the device level and then move it rapidly to cloud-based platforms for storage—thereby eliminating the need to retain it locally
- Program selected IoT data analytics to execute workloads locally, helping reduce or eliminate the need to return many capabilities round-trip to federated computing clusters in the cloud
- Set up IoT-enabled applications so they perform spatiotemporal, sensor-data analysis at the IoT endpoint, and send the rest of the data to an IoT-based data lake or log database for further analysis, storage and archiving
- Cleanse incoming sensor data at the IoT endpoints, such as by imputing missing values, and then forwarding it to an IoT gateway for cross-endpoint normalization, aggregation, inference and analysis
- Make the most of the massively parallel computing power of the cloud computing clusters at the heart of distributed IoT environments
- Scale IoT-enabled applications to support any size, volume and speed of data from any IoT-enabled device, anywhere on the planet
- Source data from any database, device, middleware fabric, sensor and stream on the IoT platform
- Distribute execution of analytics algorithms dynamically out to disparate IoT-enabled edge devices and gateways to maximize end-to-end application speed, throughput and agility
- Expose a functional API that helps simplify development, testing and deployment of algorithms and other complex application logic artifacts that are being deployed to the edges of a complex IoT-enabled application
- Aggregate a library of prebuilt IoT algorithms, maintained across federated repositories, to speed developer productivity in the building and maintenance of edge applications
To witness the next step in the evolution of IoT analytics, attend IBM InterConnect 2017, 19–23 March 2017, in Las Vegas, Nevada. Learn about the Bluemix cloud platform’s rich development environment for team data science, and discover how to rapidly scale your business with infrastructure, Watson, software and services. Register to join large enterprises, highly innovative new start-ups and the world’s foremost technical experts at IBM InterConnect 2017.