Launch of Teraki’s Platform Services

Introducing Teraki Platform to complement our existing Teraki Device SDKs to effortlessly streamline the development of embedded applications. By bridging the sensor devices to the cloud, in order to deliver the best customer experience for any targeted use case.

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Reducing the emission curve

Transition to electro mobility complemented by better utilization of cars with efficient software will help pull to down the emission curve. While 80% of data collected and processed in data servers is discarded afterwards

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Remote Driving

Ideally a self-driving car should drive without any intervention, in current reality there will be so-called 'edge cases': situations where the AD perception stack doesn’t know what it should do.

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New technologies can help to 'combat' the impacts of the Corona virus

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.

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SLAM Technology

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.

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Cameras, the eyes of the future

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.

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'GREEN' SOFTWARE REDUCES CO2 EMISSIONS: 1/3 TON PER CAR PER YEAR

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.

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How to obtain optimal sensor fusion results

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

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LiDAR & Camera: a strong marriage

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.

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Meet the new Teraki DevCenter

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.

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Making lossy compression practically lossless

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

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Sensor fusion's role in autonomous vehicles

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,

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Video pre-processing: moving from human to machines

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,

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How will Semi-Autonomous Driving change a car's costs per mile?

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).

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Autonomous Car's Big Problem

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?

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Save lives and money by listening to your car

Driver behavior information can directly lower insurance premiums, fuel costs, depreciation as well helps to lower the number of accidents and ultimately save lives.

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Save money by listening to your car

Directly after a car has been bought, an additional set of ongoing cost kick in. Owning a car will face the car owner and fleet manager with significant additional costs.

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What are the most reliable algorithms for processing automotive sensor data on the edge?

Comparing Teraki's ‘Intelligent Edge Processing' with Filtering, Sampling and Compression. A quantitative and qualitative analysis.

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How to train and update your models faster?

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.

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Reduce video processing with an additional 75% and retain high detection rates.

In this blog we share with you how we achieve significant data reductions in the video stream without compromising the predictive power of the car's perception stack.

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Why Edge Computing is key for the automotive industry

Edge computing is not a new technology, but It is now starting to realise its true potential in the real-time data transfer from device to cloud and in real-time data processing at the device.

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