Category Archives: Blog with BEBdata

AI is Listening

BEBDATA BLOG AI IS LISTENINGArtificial Intelligence (AI) is able to measure tone, tempo and other voice characteristics. Some systems compare those sounds to stored speech pattern libraries that define a plethora of human emotions to determine an individual’s emotional, mental or even physical health.

When this sound technology is used in conjunction with computer vision, the science that allows computers to gain a high-level understanding from digital images or videos, the applications become even more powerful. For example, imagine a vehicle that is able to hear a driver yawning and see the driving dozing off.

Research firm Gartner Inc predicts that within three years, 10% of personal devices will have emotion AI capabilities that include wearables (similar to a Fit Bit) that is able to monitor an individual’s mental health or video games that adapt to the players mood.

USPS Driverless Test Rest Run

BEBDATA USPS DRIVERLESS TEST RUNLast year, the US Postal Service entered into a contract with self-driving truck startup TuSimple to haul mail between Dallas and Phoenix. Founder, Xiaodi Hou says that this USPS pilot gives them fuel to help validate their system and expedite the technological development and commercialization progress.

TuSimple completed five round trips between May 28 and June 10 of 2019 while a safety engineer and licensed driver ride along in the cab. Its Level 4 self-driving system (see below for self-driving categories defined), uses 8 cameras to detect cars, pedestrians, and other obstacles over one-half a mile away, even in inclement weather.

TuSimple’s camera-based system allows it to achieve three centimeter (1.18 inch) precision for truck positioning even in inclement weather and tunnels with real-time decision making. By keeping aware of traffic flow ahead, trucks are able to maintain a given speed more consistently than human drivers which can cut fuel consumption by as much as 15%.

The USPS has been interested in self-driving technology for a long time. In 2017, a report published by the Inspector General detailed plans to add semi-autonomous mail trucks to its fleet as early as 2025. Placed into service on 28,000 rural routes, they would free up about 310,000 postal workers to sort and deliver packages.

TuSimple has R&D labs in San Diego and test facilities in Tuscon. It expected to close out 2019 with a 200-truck fleet in the US and a 300-truck fleet in China, making it the largest self-driving truck solutions company in the world.

Later the same year, TuSimple operated several self-driving trucks for 22 hours each along the I-10, I-20, and I-30 corridors through Arizona, New Mexico, and Texas. It says freight along the I-10 corridor accounts for 60% of the US’s total economic activity. It expects its semi-autonomous trucks to be a frequent sight along that route in the months ahead.

Self-Driving Systems are categorized by five-levels:

Level 1- Driver Assistance-Under specific conditions, the car controls either the steering or the vehicle speed, but not both simultaneously. The driver performs all other aspects of driving and has full responsibility for monitoring the road and taking over if the assistance system fails to act appropriately. Cruise control is Level 1

Level 2- Partial Automation- The car can steer, accelerate, and brake only in certain circumstances. Maneuvers such as responding to traffic signals or changing lanes largely fall to the driver, as well as scanning for hazards.

Level 3- Conditional Automation-The car is able to manage most aspects of driving, including monitoring the environment. The system prompts the driver to intervene when it encounters a scenario it can’t navigate. The driver must be available to take over at any time.

Level 4 -High Automation-The vehicle can operate without human input or oversight but only under select conditions defined by factors such as road type or geographic area. In a shared car restricted to a defined area, there may not be any. But in a privately owned Level 4 car, the driver might manage all driving duties on surface streets then become a passenger as the car enters a highway.

Level 5- Full Automation-The vehicle can operate on any road and in any conditions a human driver could negotiate.

Descriptive Analytics

Descriptive analyticsDescriptive analytics is a preliminary stage of data processing that creates a summary of historical data to yield useful information and prepare the data for further analysis. Descriptive analytics is sometimes said to provide information about the past or what happened.

The vast majority of the statistics used today fall into this category. (Like sums, averages, or percentages).  For all practical purposes, there are an infinite number of these statistics. Descriptive statistics are useful to show things like, total stock in inventory, average dollars spent per customer and Year over year change in sales. Common examples of descriptive analytics are reports that provide historical insights regarding the company’s production, financials, operations, sales, finance, inventory and customers.

Predictive Analytics Defined

BEBDATA BLOG PREDICTIVE ANALYTICSPredictive analytics encompasses a variety of statistical techniques from data mining, predictive modelling, and machine learning, that analyze current and historical facts to make predictions about future or otherwise unknown events.

Predictive models identify patterns found in historical or transactional data to identify risks and opportunities. Models capture relationships among multiple factors to allow assessment of risk or potential associated with a particular set of conditions. The defining functional effect is a predictive or probability score for each.

One of the best-known applications is credit scoring, which is used throughout financial services. Scoring models process a customer’s credit history, loan application, customer data, etc., in order to rank-order individuals by their likelihood of making future credit payments on time.

Prescriptive Analytics – What Is It?

Prescriptive analytics goes beyond predicting future outcomes by also suggesting actions to benefit from the predictions and showing the implications of each decision option.

Prescriptive analytics not only anticipates what will happen and when it will happen, but also why it will happen. Further, prescriptive analytics suggests decision options on how to take advantage of a future opportunity or mitigate a future risk and shows the implication of each decision option. Prescriptive analytics can continually take in new data to re-predict and re-prescribe, thus automatically improving prediction accuracy and prescribing better decision options. Prescriptive analytics ingests hybrid data, a combination of structured (numbers, categories) and unstructured data (videos, images, sounds, texts), and business rules to predict what lies ahead and to prescribe how to take advantage of this predicted future without compromising other priorities.

2020 Auto Trends – Download upgrades to your car

Automakers must invest in upgrades to the digital platforms within new cars. Earlier this year, BMW introduced a wireless service for some of its models. Just like regular software updates, the new service keeps the operating system up-to-date with the latest version.

This new service includes an intelligent personal assistant that can be expanded automatically and OTA (Over The Air).

Some other manufacturers also offer wireless OTA software updates that include Tesla, Audi, Volvo, and Ford. Most have updates that are focused on non-critical infotainment features or offed new applications and functions for the infotainment system.

 

2020 Auto Trends – Automation

Self-Driving Systems are categorized by five-levels:

Level 1- Driver Assistance: Under specific conditions, the car controls either the steering or the vehicle speed, but not both simultaneously. The driver performs all other aspects of driving and has full responsibility for monitoring the road and taking over if the assistance system fails to act appropriately. Cruise control is Level 1

Level 2- Partial Automation: The car can steer, accelerate, and brake only in certain circumstances. Maneuvers such as responding to traffic signals or changing lanes largely fall to the driver, as well as scanning for hazards.

Level 3- Conditional Automation: The car is able to manage most aspects of driving, including monitoring the environment. The system prompts the driver to intervene when it encounters a scenario it can’t navigate. The driver must be available to take over at any time.

Level 4-High Automation: The vehicle can operate without human input or oversight but only under select conditions defined by factors such as road type or geographic area. In a shared car restricted to a defined area, there may not be any. But in a privately owned Level 4 car, the driver might manage all driving duties on surface streets then become a passenger as the car enters a highway.

Level 5- Full Automation: The vehicle can operate on any road and in any conditions a human driver could negotiate.