bike


AI and IoT: Taking Data Insight to Action - DZone IoT

#artificialintelligence

Recent Gartner estimations lead us to believe that up to 20 billion connected things will be in use by 2020. Data is the oil of our century -- but should we be concerned with a "data spill hazard"? Will artificial intelligence curb this threatening phenomenon, or rather, will it reveal the full potential of IoT data value? If my calculations are correct, when artificial intelligence hits the Internet of Things... you're gonna see some serious sh*t." The question is no longer whether companies should embrace big data analytics technologies.


Watch: This motorcycle-riding robot is no match for one of the most successful racers of all time

ZDNet

We all know the robots are coming. That probably inspires some complicated feelings. So, it's comforting when a three-year development effort to make a robot that can set a speed record results in a human victory... by a wide margin. Yamaha and robotics developer SRI have been working on a humanoid that can ride an unmodified motorcycle. The goal was to beat the lap times of one of the most successful motorcycle racers of all time, Valentino Rossi.


OracleVoice: How Emerging Technologies Are Beginning To Transform Customer Service

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Customer service can be frustrating for consumers, expensive for businesses, and time-consuming for both. But emerging technologies on the cusp of wide adoption--including augmented reality, the Internet of Things, and AI-powered virtual assistants--offer the potential to transform the customer experience while reducing cost. Demonstrations at Oracle OpenWorld in San Francisco provide a glimpse of where things are heading. In one example, a Wi-Fi-enabled Yamaha dirt bike showed how augmented reality could reshape the way field service technicians and owners work on machines. The motorbike essentially operates as an IoT device on wheels, uploading health and status information daily that is integrated into Oracle Service Cloud.


Mussel-inspired plastic could make self-repairing body armour

New Scientist

A new material inspired by mussels is flexing its muscles. It can stretch without snapping and repair its own molecular bonds, so it could be useful in robot joints that lift heavy objects, or for packaging to protect delicate cargo from accidental falls. Mussels and some other molluscs hang onto solid surfaces using an adhesive protein and tough, plasticky fibres, which are extremely strong and can repair themselves when a few molecular bonds within them are broken. For a mussel, these stretchy yet strong fibres come in handy when a wave hits. Megan Valentine at the University of California, Santa Barbara, and her colleagues created a plastic with these same properties by mimicking the chemistry the mussels use.


sony-future-lab-next-hit

Engadget

That's because this was the fourth and final meetup for participants of "Program N," a project where volunteers tested a hands-free open-ear audio device (called, appropriately enough, Concept N) for Sony for almost a year. Aside from paying their own money for the hardware, Program N participants were invited to attend several meetups throughout the year, where they interacted with Sony engineers directly. Future Lab also attended the Silicon Valley Bike Festival and Bike To Work Day SF in order to talk to cyclists and bike commuters about how N could improve their experience. "The first version of N didn't have a calling function," said Okamoto, adding that most people in Tokyo don't use headsets to make calls, so it was an afterthought.


AI could help reduce bike accidents

#artificialintelligence

When I found out a company called Tome Software was going to start a trial that uses AI to reduce bike accidents, I took note. The company will start by testing real cyclists using Trek bikes at the University of Michigan's TechLab at Mcity. It plans to focus on what Jake Sigal, the CEO for Tome Software, told me is the most common type of accident -- a car hitting a bike from the side or behind. For me, it's an interesting project because it means reducing bike accidents by warning both the cars and those on bikes in the most dangerous intersections.


Global Bigdata Conference

@machinelearnbot

I started biking on a regular basis last summer. Most of the work in machine learning is focused on things like smart home integrations, automated cars, Facebook bots, and apps that make it easier to travel or check the weather forecast. It plans to focus on what Jake Sigal, the CEO for Tome Software, told me is the most common type of accident -- a car hitting a bike from the side or behind. It will correlate several data sets -- in the most common areas where a bike could be in danger, the AI will examine factors like time of day (bright sun at dawn), road characteristics (such as the speed limit and berm width), and existing crash data from cars and cyclists in that area.


Usage patterns of Dublin Bikes stations – Towards Data Science – Medium

@machinelearnbot

I collected data every 2 minutes from a public API from January 2017 to August 2017 to build up a decently sized historical data set from which we can work out typical weekday usage profiles for each of the 108 stations. It's straightforward to see that stations most closely fitting the green line would typically be used for commuting into the city to the blue stations in the morning, so naturally we'd expect that green stations would be found in residential areas and blue stations in the city centre. While this is what you'd expect to see I was surprised by just how clear the clusters really were -- the blue stations are focussed around the Dublin 2 area where a lot of business offices are based, bordered by the in-between reds, and green stations outside the city centre in more residential areas. I collected weather data for Dublin simultaneously when querying the bikes API to build the dataset used for this post, so it'd be interesting to look at its effect on the usage patterns and perhaps build some predictive model for each station.


An Italian scooter maker invents a robot that follows you around carrying your stuff

#artificialintelligence

The company is about to begin testing Gita in a number of industrial settings, including factories and theme parks. Piaggio created Piaggio Fast Forward 18 months ago. The sensors, control systems, and electric propulsion used in the new robot could all prove crucial for future Piaggio products, says Michele Colaninno, chairman of the board of Piaggio Fast Forward. Still, as with many of the ideas being tested by transportation companies, including self-driving taxis, semi-automated trucks, and delivery drones, the underlying technology, as well as the potential applications, remain a bit unproven.


An Italian scooter maker invents a robot that follows you around carrying your stuff

#artificialintelligence

The company is about to begin testing Gita in a number of industrial settings, including factories and theme parks. Piaggio created Piaggio Fast Forward 18 months ago. The sensors, control systems, and electric propulsion used in the new robot could all prove crucial for future Piaggio products, says Michele Colaninno, chairman of the board of Piaggio Fast Forward. Still, as with many of the ideas being tested by transportation companies, including self-driving taxis, semi-automated trucks, and delivery drones, the underlying technology, as well as the potential applications, remain a bit unproven.