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Big Data and Cloud Computing - The Next Step for Robot Intelligence
By Ayanna Howard, CTO, Zyrobotics, LLC
The Robots are coming! The Robots are coming! The Robots are already here. In recent months, there has been an upsurge in the attention given to robots and artificial intelligence (AI) and their inevitable destruction of the human race if we are not watchful. Whether your opinion sits on one side or the other, the fact remains; robots have already become a part of our society and, in some cases, an integral part. No longer is a robot chauffer, i.e. an autonomous robot car that can drive an individual to work, a whimsical thought of a science-fiction movie director. No longer is a robot suit, i.e. a robot exoskeleton that can assist a paraplegic to walk, a fantasy story of a writer. Not to argue against being vigilant (because ethical considerations concerning the inclusion of new technology in society should always be a part of the discussion), but coupled with the doom-and-gloom messages of robots and AI, robots, with intelligence, are also being seen as beneficial, life-saving, machines for assisting us in our everyday lives. Telepresence robots, such as the RP-VITA, are transforming health care delivery in the hospital setting and are being used in medical applications ranging from newborn care to stroke treatment. Wearable robotic exoskeletons, such as the ReWalk exoskeleton, are helping paralyzed patients stand up and walk in the home environment. And a host of startup companies, such as Zyrobotics, are working on the next generation of therapy robots for children.
“Big data and Cloud computing have become the next big step for robot intelligence”
So, what’s the next step? How do these robots continue to grow as our personal helpers, assistants, and workers? How do we ensure that robots, personalized robots, understands our every needs–whether it’s to avoid certain roads because driving on the freeway unnerves a person or to increase the support provided by a exoskeleton because the user wants to directly interact with her young, active, children. A surprising answer to this is the rising utilization of Big Data and Cloud computing technologies. Even today, there are numerous efforts focused on integrating Cloud services with robots. From smart robot toys powered by IBM’s Watson artificial intelligence system to robots that use YouTube to learn how to cook, robots are capitalizing on the availability of Cloud-based resources. Through the use of services such as WikiHow, YouTube, and Google maps, robots are learning and will one-day share back the information they have learned. For an autonomous robot car, it’s an easy sell to consumers that Cloud-based technologies are useful–we are used to having our GPS location stored and sharing information about traffic accidents via our smartphones. Even for a future robot exercise coach, it would seem reasonable for us to freely have our robot coach upload our activity data to the Cloud–we’re used to having wearable fitness trackers such as Jawbone and Fitbit personalize our experience based on this type of Cloud-powered data smarts. In general, for applications that we’re currently comfortable with, freely uploading information about our habits to the Cloud has not resulted in an obvious security or privacy concern to most of us (as of yet).
Yet, what about Cloud technologies for robots in healthcare, such as surgical robots, therapy robots for children, or exoskeletons? Although Big Data for health is still in the early stages of development, in developing algorithms for predictive analytics or in implementing HIPAA- compliant data collection efforts, Cloud technologies have the potential to drastically change the health care environment. Robots for healthcare are no exception to this. Cloud technologies can allow telepresence robots to collect their user’s health status indicators and, with guidance from doctors, provide reminders to enhance medication adherence. Cloud technologies can allow therapy robots to collect statistics on children, especially those related to infants and toddlers at risk for developmental disabilities, and monitor for early warning signs that can be transmitted to clinicians. A surgical robot can connect to the Cloud t o provide assistance to surgeons, while in the operating room, as it mines through the large sets of open fMRI data associated with patients with similar medical conditions. In the not-so-distant future, healthcare robots should be able to access the personal Cloud data stream associated with their user and collected from their exercise band, their Smartphone GPS coordinates, and their text conversations to provide counseling to teenagers who might be depressed. The challenges for these types of applications are similar in nature to those for Big Data for health. While the healthcare industry continues to expand their use of Big Data and Cloud computing technologies, security and privacy issues remain a prime challenge. By collecting massive amounts of health data from multiple sources, both healthcare robots and healthcare professionals will be better equipped to address the needs of their users, but this data is also extremely sensitive. Currently, there is no gold standard for addressing these issues for healthcare robots, but as robots continue to move into the healthcare space, receiving FDA clearance and being provided access to HIPAA compliant data, these issues must be tackled. Possible solutions might include innovative ways for users to opt-in during robot interaction or scrubbing shared information so it is de-identified to everyone but the robot helper. Whatever the solution, just as the challenges and opportunities afforded by embracing Big Data for healthcare continues to expand, its role in healthcare robots will also continue to grow. Big data and Cloud computing have become the next big step for robot intelligence.