The coronavirus outbreak has led to country lockdowns, shutting of borders, school closures, restaurants shutdowns, and cancellation of events. Across the globe companies are using technology to fight the impacts of the virus.
SLAM is the best method to address the precise mapping of the physical world. Even though the technology is in nascent stage now, accurately projecting and mapping the physical world virtually opens the door to plenty of innovative applications.
AI cameras, or computational photography, is a staple of the modern smartphone market. Nearly every smartphone uses some form of AI to help the pictures look better. The future of photography will be more computational than optical of nature.
The sensors and sensor processors are by far the highest contributors of power consumption of Autonomous Driving. Going autonomous demands more power that will be taken from battery. Three cars running autonomously for a year in can produce from 1.3 to 0.2 Tons CO2 per year depending on the spec.
Autonomous driving algorithms detect and label objects in streams of complementary types of data. In general it is easier to detect objects in point clouds, than it is to identify correctly their type. An image can identify easily what object is in it, but it is more complicated to build a bounding box around the object
Each sensor that captures reality, has its own advantages and disadvantages. In this case, LiDAR is an accurate sensor to measure distance. The camera on the other hand, can capture visual reality and clearly show details as well colours.
With the new improved look and feel, we've been working hard on Teraki's DevCenter in the recent months. DevCenter demonstrates Teraki's capabilities for data reduction to automate accurate and highly efficient EDGE analytics.
Much like our eyes looking to the stars and for our brains to recognise what the star constellations are, capturing reality through cameras and sensors requires computer intelligence to recognise objects
According to recent CB Insights, 46 corporations are working on Autonomous Vehicles (AV) technologies and it is expected that the AV-market will grow from $54B to $556B in 2026. Next to its large market size,
Alongside the development of autonomous driving (AD) and Advanced Drivers' Assistance Systems (ADAS), the requirements for storage, processing and transmitting data are rapidly increasing. On the other hand,
Most people will have heard how autonomous driving will improve mobility and safety, but did you know about the costs saved by autonomous driving? In this blog we will describe why costs will be lowered with the implementation of (L2-L4).
Electric car manufactures promote fully autonomous driving (AD) at levels 4 and 5 (L4/L5) as a way to improve the car's mileage reach for the same charge of its electric battery. But is that really the case?
DevCenter is Teraki's free and one-stop-shop portal for customers to test Teraki's technology with their own sensor data. Next to testing the Teraki technology, DevCenter is also used by customers in their production environments as a tool to train and add new sensors or signals to their data collection campaigns.