FLIR Systems, based in Oregon State Barlow, USA, is a sensor company focused on the production of thermal imaging products for a wide range of applications, according to Mams, who recently announced a significant strategic investment in the Singapore machine Learning and Artificial intelligence (AI) startups Cvedia. The Syncity Simulator software tool developed by Cvedia provides an ultra-realistic multi-mode digital environment for automated System OEMs and related sensor manufacturers to train their systems faster, safer and more economically than traditional data acquisition technologies. Cvedia's syncity simulator software can demonstrate the physical characteristics of the real world; Simulate a variety of lighting and environmental conditions; In the rendering of objects such as people, animals and automobiles, artificial intelligence systems are used to translate them into realistic and realistic objects.
This results in high-quality datasets that, when entered into the customer's neural network framework, can significantly shorten the training time of these deep learning systems and simplify the training process. Unless you're a sensor geek, this message may seem like a little news. But the move shows a new reality in the increasingly competitive sensor market, as well as in the AI and machine learning boom: for small businesses, focusing on good hardware is not enough;
But even startups, with a choice of direction and the use of intelligent AI engines to package their hardware, can thrive in a market giant's ring.
syncity simulator software for thermal imaging maps to protect wildlife FLIR provides thermal imaging sensors for a variety of enterprise applications, such as on-site inspections and fire fighting. Its sensors are available in a variety of applications, including tablets and smartphone accessories.
Recently, the company has been advocating that autonomous vehicles running on LIDAR and visible light cameras have blind spots that can be solved using thermal imaging cameras. This poses a marketing challenge for FLIR, and convincing autonomous car developers to use thermal imaging cameras on autonomous vehicles is not easy and challenging, but how can flir prove that their products are the preferred thermal sensors for autonomous driving applications?
Because there are other thermal sensing companies in the ecosystem, such as rival Adasky. According to Mams Consulting previously reported that the Israeli manufacturer Adasky was founded in January 2016, has launched a far infrared camera viper--industry's first embedded machine learning software in the far-infrared solid-state camera, without any moving parts, and capable of data processing inside the camera, can help level 3
, 4 and 5 self-driving cars get to market faster. FLIR's answer is to invest in the second company, Cvedia, to differentiate its thermal imaging sensors using the latter's plug-and-play AI and machine learning functions related to autonomous driving, such as object recognition.
FLIR believes it will become the most attractive supplier of thermal imaging sensors for autonomous driving applications if it is able to ensure that its sensors are adapted to a wide range of autonomous driving architectures while being able to take part in the development burden of a self-driving vehicle developer. This is in contrast to the traditional operating model typically used by sensor vendors, where the traditional model is to produce task-independent sensors for as many applications as possible.
It also suggests that the sensor market is tightening.
Focus on traffic sensing, integrated AI and machine learning for 3D Vision sensor manufacturers Viscando We have also focused on other sensor companies, packaging their hardware and application-specific features together. For example, Viscando company, which specializes in manufacturing 3D vision sensors.
With the launch of the Intel built-in AI engine's RealSense 3D vision camera, the 3D Vision Sensor market is becoming more and more difficult.
Viscando Company uses 3D vision and AI to achieve accurate traffic data But Viscando continues to remain competitive by focusing on a niche industry-a variety of municipal traffic sensors. Viscando has created a better product portfolio than a simple 3D camera, including AI and machine learning features related to traffic sensing applications.
The niche market is enough to keep viscando growing, but it's small enough that a giant like Intel hasn't developed it specifically for it. Without embedded AI and machine learning, Viscando will not be able to compete with Intel or any other 3D vision provider, but it will be competitive enough to build a stack of AI and machine learning for a particular domain on a hardware basis.
This tells us that the sensor market for hardware startups still has ample market space in the event of a plunge in sensor prices, but only if these small businesses are willing to focus on and look for strategic opportunities to develop intelligent capabilities on their hardware.
This is the strategic purpose of FLIR's investment in Cvedia. ' This investment in Cvedia will enhance our ability to innovate our sensing solutions, enabling our customers to make mission-critical decisions faster and more accurately, ' said James Cannon, president and CEO of FLIR, ' who can automatically notify users of critical information or the addition of software algorithms to the system, is a valuable feature that greatly strengthens the unique and rich data that our sensors perceive.
' FLIR's investment in AI companies | Or can inspire the thermal imaging products how to play
