sensor


The 25 Ways AI Can Revolutionize Transportation: From Driverless Trains to Smart Tracks

#artificialintelligence

With massive breakthroughs in smart technologies being reported every month, it won't be long until our transport industries are dominated by AI. Here are just some of the ways artificial intelligence is changing the face of transport, and what we can expect in the near future. Autonomous cars have quickly moved from the realm of sci-fi into reality. Though still in the early stages, these AI-driven vehicles could drastically change how we get from A to B in the near future. From plowing snow to collecting garbage, self-driving trucks could soon be taking over a lot of our dirty work.


TuSimple logs Level 4 autonomous test miles

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TuSimple, a 30-month-old San Diego-based autonomous truck startup, says it is currently testing three Class 8 Peterbilt trucks in Arizona and has already achieved more than 15,000 Level 4 autonomous test miles using its computer vision system. Level 4 autonomy (on a scale of 1 to 5) doesn't require any action by a human driver and is widely considered the first level of "fully autonomous" driving. Chuck Price, TuSimple vice president of product, says the company's advanced vision system uses up to ten cameras in conjunction with sensors, GPS, three millimeter wave radar units and automated HD mapping to achieve a sensing range of up to 300 meters – three-times the range of standard LiDAR. "[LiDAR] is powerful in that you can get your perception problems solved very quickly … however, the perception quality of LiDAR is lower resolution and the sensor itself is very expensive and doesn't have the range that we can get from our [camera] sensor," he says. "We don't believe any competitors can launch a commercial product with a LiDAR solution.


Huawei P20 Pro review: The best phone you'll never buy

Engadget

For the past few months, Huawei has been making headlines for all the wrong reasons -- the US government warned against buying the company's phones, which led to the breakdown of near-final deals with AT&T and Verizon. Then Best Buy, one of its few US retail partners, backed away too. We're not sure if the concerns hold any weight, but one thing is clear: It sucks to be Huawei right now. And in the midst of that turmoil, Huawei revealed its new P20 Pro, a remarkably well-built device with a triple camera system and loads of style. I doubt that would ever win over a Sinophobic bureaucrat though, so there's a strong chance no one in the US will ever be able to walk into a store and buy one.


Till the cows come home takes on new meaning with artificial intelligence

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A cow stands in a pasture on Seven Oaks Dairy in Waynesboro, Ga. On the cow's neck is a device called IDA, or "The Intelligent Dairy Farmer's Assistant," created by Connecterra. It uses a motion-sensing device attached to a cow's neck to transmit its movements to a program driven by artificial intelligence. SAN FRANCISCO (AP) -- Is the world ready for cows armed with artificial intelligence? No time to ruminate on that because the moment has arrived, thanks to a Dutch company that has married two technologies -- motion sensors and AI -- with the aim of bringing the barnyard into the 21st century.


Predicting physical activity based on smartphone sensor data using CNN LSTM

#artificialintelligence

Today we want to look at how smartphones, smart-watches and the like are able to predict what kind of activities you're doing based on sensor data and try to reproduce this process. The possibilities range from sport or health applications to games like Pokémon Go, to name a few. Most modern smartphones have an accelerometer and a gyroscope. An accelerometer measures changes in velocity and changes in position, whereas a gyroscope measures changes in orientation and changes in rotational velocity. For this task we use a dataset from UCI.


Five Challenges of Analyzing Internet of Things (IoT) Data - International Institute for Analytics

@machinelearnbot

The analysis of Internet of Things (IoT) data is quickly becoming a mainstream activity. I've written about the Analytics of Things (AoT) before (some examples here, here, and here). For this blog, I'm going to focus on a few unique challenges that you'll most likely encounter as you move to take IoT data into the AoT realm. With many historical data sources, such as transactional data, it was often quite an effort to gather the source data required for analysis. It was necessary to identify what information was available, how it was formatted, and also to reconcile data from different sources that often contained similar information, but had inconsistencies in how it was provided.


Researchers design 'soft' robots that can move on their own: Using sensors, actuators and artificial muscle, robots could be used in medicine, rescue and defense

#artificialintelligence

Cunjiang Yu, Bill D. Cook Assistant Professor of mechanical engineering, said potential applications range from surgery and rehabilitation to search and rescue in natural disasters or on the battlefield. Because the robot body changes shape in response to its surroundings, it can slip through narrow crevices to search for survivors in the rubble left by an earthquake or bombing, he said. "They sense the change in environment and adapt to slip through," he said. These soft robots, made of soft artificial muscle and ultrathin deformable sensors and actuators, have significant advantages over the traditional rigid robots used for automation and other physical tasks. The researchers said their work, published in the journal Advanced Materials, took its inspiration from nature.


When Will That Happen? A Novel Approach to Time Series Prediction - Emcien

#artificialintelligence

Knowing when something will happen – not simply that it will happen – can better enable you to take the right action at the right time in response to a prediction. As a result, you can make a bigger impact to the outcome you want to improve. That's why it's so valuable to analyze time series data and make time series predictions. But it typically refers to a type of time series prediction in which you estimate or project the value of a single variable, or multiple variables, at various points in time in the future. For example, many businesses forecast sales (variable) figures (value) each week for the quarter (time).


When Will That Happen? A Novel Approach to Time Series Prediction - Emcien

#artificialintelligence

Knowing when something will happen – not simply that it will happen – can better enable you to take the right action at the right time in response to a prediction. As a result, you can make a bigger impact to the outcome you want to improve. That's why it's so valuable to analyze time series data and make time series predictions. But it typically refers to a type of time series prediction in which you estimate or project the value of a single variable, or multiple variables, at various points in time in the future. For example, many businesses forecast sales (variable) figures (value) each week for the quarter (time).


Thermal Imaging Cameras Could Keep Self-Driving Cars Safe

WIRED

After Uber's fatal self-driving crash last month in Tempe, Arizona, most observers had two basic question: Why did the car not see Elaine Herzberg crossing the street and stop before hitting her? And how can we stop this happening again, to someone else? The ride-hailing company has indefinitely suspended its testing program, and is cooperating with the National Transportation Safety Board's investigation of the crash. The NTSB hasn't revealed any findings yet, but the lidar--the laser-shooting sensor that should have spotted Herzberg, even in the dark--is an obvious focus. Maybe it had a blind spot, or lacked the resolution to identify Herzberg as a pedestrian.