IBM hosted an artificial intelligent (AI) event at its Munich Watson IoT HQ, where it underlined its claim as a leading global AI and internet-of-things (IoT) platform providers in the enterprise context. AI and the IoT are both very important topics for enterprise users. However, there remains some uncertainty among enterprises regarding the exact benefits that both AI and IoT can generate and how businesses should prepare for the deployment of AI and IoT in their organizations.
One year into the launch of its Munich-based Watson IoT headquarters, IBM invited about one thousand customers to share an update of its AI and IoT activities to date. The IBM “Genius of Things” Summit presented interesting insights for both AI and IoT deployments. It underlined that IBM is clearly one of the leading global AI and IoT platform providers in the enterprise context. Some of the most important insights for me were that:
AI solutions require a partner ecosystem. IBM is well aware of the fact that it cannot provide IoT services on its own. For this reason, IBM is tapping into its existing partner ecosystem. Those partners are not only other vendors. IBM’s ecosystem partnership approach embraces also customers such as Schäffler, Airbus, Vaillant, or Tesco. The event demonstrated how far IBM has matured in living and breathing customer partnerships in the IoT solutions space. For instance, IBM’s cooperation with Visa regarding secure payment experiences for any device connected to the IoT is an example of a new quality of ecosystem partnership.
A few days ago, at an event hosted by Continental, Deutsche Telekom AG, Fraunhofer ESK, and Nokia Networks, I came across an interesting example of an emerging mobile Internet-of-Things (IoT) solution: the initiative to “connect the Autobahn” in Germany. The goal of the Digitales Testfeld Autobahn initiative is to develop a platform that allows a wide range of players to access a common platform for digital services in the context of Germany’s road infrastructure. The event also included a test drive to highlight how driving “assistants” in connected cars could communicate with a latency of about 15 milliseconds. Discussions at the event underlined several insights that CIOs should consider when devising mobile IoT solutions:
Ecosystem partnerships create more value for IoT solutions than standalone approaches. At the event, Deutsche Telekom’s CEO, Continental’s Head of Interior Electronic Solutions, Nokia’s VP of Strategy, Fraunhofer-Institute’s Head of Embedded Systems, and Germany’s Minister for Transport all pointed to the necessity for close cooperation to make the “digital Autobahn” platform work. Proprietary OEM technologies will not boost the connected road infrastructure. Continental told us that open IoT systems create more value than closed systems for the company and its customers. To uncover its true potential, the “digital Autobahn” platform will also need to be open to third parties like weather forecasters, retailers, and entertainment companies. This means that CIOs need to support open APIs.
I recently attended IBM BusinessConnect 2015 in Germany. I had great discussions regarding industrial Internet of Things (IoT) and Industrie 4.0 solutions as well as digital transformation in the B2B segment. One issue that particularly caught my attention: edge computing in the context of the mobile IoT.
Mobility in the IoT context raises the question when to use a central computing approach versus when to use edge computing. The CIO must decide whether solution intelligence should primarily reside in a central location or at the edge of the network and therefore closer to (or even inside) mobile IoT devices like cars, smart watches, or smart meters. At least three factors should guide this decision:
Data transmission costs. The costs of data transmission can quickly undermine any mobile IoT business case. For instance, aircraft engine sensors collect massive amounts of data during a flight but send only a small fraction of that data in real time via satellite connectivity to a central data monitoring center while the plane is in the air. All other data is sent via Wi-Fi or traditional mobile broadband connectivity like UMTS or LTE once the plane is on the ground.
Mobile bandwidth, latency, and speed. The available bandwidth limits the amount of data that can be transmitted at any given time, limiting the use cases for mobile IoT. For instance, sharing large volumes of data about the turbines of a large container ship and detailed inventory measurements of each container on board is completely impractical unless the ship is close to a coastal area with high mobile broadband connectivity.