The Internet of Things is the universe of objects that are–or could be–instrumented and connected to computer networks. They include everything from monitoring devices attached to electrical grids to RFID tags on boxes of merchandise to video cameras surveying city streetscapes to smart phones nestled in a purse or pocket. The emergence of the Internet of Things gives rise to a tremendous opportunity: Fed with a continuous stream of information from all of these things–potentially trillions of devices–we can know more completely what is really happening in the world around us than our ancestors could have imagined.
To fulfill this vision, though, a lot of elements must come together: instrumented things, ubiquitous networks, and the capability to capture, store and analyze the data–often in real time. And there’s the big challenge. “If you don’t have the right data collected at the right place and the right time with the right frequency, you can’t do the smart analysis,” says Xiaowei Shen, associate director of IBM Research – China, in Beijing.
The China lab has the job of solving these problems. Starting early this year, the lab was put in charge of leading IBM’s worldwide efforts to develop technologies and explore new business opportunities that can help organizations of all types get the maximum benefit out of the Internet of Things. Today, the Internet of Things is the subject of the IBM Research – China Colloquium, where IBM researchers and scientists from other organizations will speak about the potential and challenges they face. The colloquium is part of an IBM Centennial program designed to convene thought leaders – including leading researchers and scientists, academics, leaders of industries, public policy makers and key IBM clients — for a series of talks and panel discussions on transformational technologies and their potential impact on the world.
IBM has had a research lab in China for sixteen years, but this initiative represents the first time that the lab has taken the lead on one of IBM Research’s so-called Big Bet projects. The colloquium does two things: It’s a progress report on what IBM has accomplished so far and on what it intends to do, and it’s an opportunity for the researchers to extend the reach of their ecosystem of partners. “This is a platform to help us build and strengthen the ecosystem, including existing partners and potential partners,” says Shen.
Creating an ecosystem is crucial because no single company, no matter how large, has the expertise and commercial reach to create Internet-of-Things solutions for entire industries by itself. The lab has established partnerships with businesses and universities, and begun working with clients on real-world problems. For example, it has launched a strategic collaboration with the Hainan Provincial Government in China with the goal of using Internet-of-Things technologies to promote economic growth–focusing on travel and tourism and food supply chain management.
The China lab has identified key technologies that IBM has already developed and targeted a set of ambitious research projects. The goal is to develop technologies and approaches to business that will surface in IBM’s hardware, software and services over the next several years. Initially, the lab will focus on China and other growth-market countries where building state-of-the-art infrastructure is a priority. The researchers will create solutions that can be deployed anywhere in the world with a minimum of customization. The initial industries targeted include energy and utilities, natural resource management and logistics and supply chain.
IBM has a good head start. It has a lot of experience in building and managing large-scale complex systems. It also has considerable capabilities in business analytics and optimization. But the technical challenges are huge. To build and manage Internet-of Things systems, IBM and its partners have to address a host of issues, including scalability, manageability, reliability, availability and security.
Consider one of the complex issues the researchers face. Large systems like this need to process data efficiently, which argues for placing a lot of intelligence outside the data centers or on the edges of the network close to the sensors. But if you do that, you have to come up with new methods for developing applications that execute different functions in widely scattered computing devices. That’s no no-brainer.
Xiaowei seems confident that the hurdles will be overcome, and aims to make progress quickly. “I’m not a patient person,” he says. Still, these technologies and the man-made systems the technologies are designed to improve are so complex that it will take many years to take full advantage of the potential in the Internet of things.