Use Case: Edge Devices

Deploy Your AI on Any Device

DeepCube’s technology allows the deployment of state-of-the-art deep learning models on edge devices, with minimal processing, memory, and battery requirements. This is critical for any edge device that requires fast response (low latency), high bandwidth (e.g. video), low battery consumption, data security and privacy (cannot send user data to cloud), and most importantly autonomous intelligence without continuous connection to the cloud.

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Deploy Your AI on Any Device

DeepCube’s technology allows the deployment of state-of-the-art deep learning models on edge devices, with minimal processing, memory, and battery requirements. This is critical for any edge device that requires fast response (low latency), high bandwidth (e.g. video), low battery consumption, data security and privacy (cannot send user data to cloud), and most importantly autonomous intelligence without continuous connection to the cloud.

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Surveillance Cameras

Intelligent surveillance cameras have become critical in monitoring and securing locations remotely. For decision making, the data has to be sent to the cloud. Tasks such as continuous monitoring of videos and crowd analysis for example pose two major problems: real-time detection and privacy. DeepCube provides the only technology that allows efficient deployment of deep learning models on surveillance cameras, enabling them to make truly autonomous decision in real-time without any connection to the cloud.

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Surveillance Cameras

Intelligent surveillance cameras have become critical in monitoring and securing locations remotely. For decision making, the data has to be sent to the cloud. Tasks such as continuous monitoring of videos and crowd analysis for example pose two major problems: real-time detection and privacy. DeepCube provides the only technology that allows efficient deployment of deep learning models on surveillance cameras, enabling them to make truly autonomous decision in real-time without any connection to the cloud.

Drones

Autonomous drones are crucial for tasks such as surveillance and reconnaissance. Today, they use deep learning models that are running on a remote cloud, which make the detection and hence decision phase impossible in real-time. Moreover, one of the key current challenges is the lack of high-quality Internet connections. With DeepCube, a deep learning model is deployed on the drone itself, enabling it to make truly autonomous decision in real-time without any need for connectivity.

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Drones

Autonomous drones are crucial for tasks such as surveillance and reconnaissance. Today, they use deep learning models that are running on a remote cloud, which make the detection and hence decision phase impossible in real-time. Moreover, one of the key current challenges is the lack of high-quality Internet connections. With DeepCube, a deep learning model is deployed on the drone itself, enabling it to make truly autonomous decision in real-time without any need for connectivity.

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Autonomous Cars

Deep learning is key for improving performance and safety of self-driving cars, which still need humans to keep an eye and take control when needed. In the real-world driving situation, prediction and decision making require a real-time control which a connectivity to the cloud does not enable. With DeepCube, a deep learning model is deployed in the car itself, enabling it to make truly autonomous decision in real-time without any need for connectivity.

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Autonomous Cars

Deep learning is key for improving performance and safety of self-driving cars, which still need humans to keep an eye and take control when needed. In the real-world driving situation, prediction and decision making require a real-time control which a connectivity to the cloud does not enable. With DeepCube, a deep learning model is deployed in the car itself, enabling it to make truly autonomous decision in real-time without any need for connectivity.

Agricultural Machines

Today, smart farming use crop disease treatments and pesticides with pinpoint accuracy via spray machines. These come equipped with computer vision and automated spray and decision has to be made on the spot. Connection to the cloud does not enable real-time decision and moreover, there can be many situations of poor connectivity quality. With DeepCube, a deep learning model is deployed in the agricultural robot itself, enabling it to make truly autonomous decision in real-time without any need for connectivity.

Agricultural Machines
Agricultural Machines

Agricultural Machines

Today, smart farming use crop disease treatments and pesticides with pinpoint accuracy via spray machines. These come equipped with computer vision and automated spray and decision has to be made on the spot. Connection to the cloud does not enable real-time decision and moreover, there can be many situations of poor connectivity quality. With DeepCube, a deep learning model is deployed in the agricultural robot itself, enabling it to make truly autonomous decision in real-time without any need for connectivity.

Transform Your Business

With DeepCube, deploy your AI on any device