Background

Technology of Interest

Computer Vision

For robotics and environmental awareness.

Computing Technology

Digital, Analog, and Quantum Computing.

LLM & Conversational AI

Chatbots, assistants, and more

Distributed Computing

Handling large-scale processes.

Chips

Analog, FPGA, and AI Inference Chips

Behavior & Activities Tracking

Embedded AIs

Edge device integration.

Spatial Perception

Intelligent navigation.

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Revolutionizing Safety and Care with Advanced Tracking Technologies

Behavioral and activities tracking at Naiscorp focuses on leveraging advanced computer vision, heat cameras, RGB-D cameras, and surveillance systems to create a comprehensive solution for security and family care. These technologies are designed to enhance safety, provide real-time alerts, and ensure better indoor monitoring for elders, children, and overall home security.

Key Capabilities

In-Door Family Tracking

In-Door Family Tracking

Monitor the movements and activities of family members, especially elders and children, to ensure their safety. AI-powered tracking systems can detect unusual patterns and provide immediate notifications.

Security Systems

Security Systems

Utilize a combination of heat and RGB-D cameras to monitor surroundings, identify unauthorized access, and detect potential threats. These systems offer proactive alerts, enabling real-time intervention in case of emergencies.

Elder Care Monitoring

Elder Care Monitoring

Track movements and detect falls or inactivity for elderly family members, providing instant alerts to caregivers or family members.

Child Safety

Child Safety

Monitor children's activities to ensure they remain in safe zones within the house and provide alerts if they wander into potentially dangerous areas.

Smart Alerts & Automation

Smart Alerts & Automation

Integrated with AI, these systems can trigger automated responses, such as locking doors, activating alarms, or notifying relevant parties based on detected events.

Why It Matters?

Enhanced Home Security

Enhanced Home Security

Ensure 24/7 monitoring of your living spaces, deterring intrusions and providing peace of mind.

Improved Caregiving

Improved Caregiving

Offer tailored solutions for elder care and child safety, ensuring their well-being and providing caregivers with actionable insights.

Real-Time Intervention

Real-Time Intervention

Proactively respond to emergencies with instant alerts and automated safety mechanisms.

Cutting-Edge Technologies

Naiscorp's Behavioral & Activities Tracking solutions are designed to provide unparalleled safety, care, and peace of mind. Contact us to learn how we can help protect your family and optimize your indoor environments with our cutting-edge systems.

Computer Vision Algorithms

Advanced AI to recognize behaviors, identify patterns, and detect anomalies.

Heat Cameras

Accurate detection of human presence, even in low-light or obscured environments.

RGB-D Cameras

Depth-sensing technology to create detailed 3D maps of spaces for better tracking and object recognition.

Surveillance Integration

Seamless integration with existing security systems for enhanced coverage.

Computing Paradigms

Digital Computing Continues to be the backbone of modern technology, with ongoing improvements in processing power and energy efficiency.
Analog Computing Recent developments have led to the creation of analog chips capable of performing AI inference tasks with significantly reduced energy consumption compared to digital counterparts.
Quantum Computing Progress has been made in reducing error rates in quantum computations, bringing practical quantum computing closer to reality.

Chips: Analog, FPGA, and AI Inference Chips

Analog Chips Advancements in analog chip design have enabled faster and more energy-efficient AI computations.
Field-Programmable Gate Arrays (FPGAs) FPGAs offer flexibility in hardware programming, allowing for customized processing architectures that can be optimized for specific tasks, including AI workloads.
AI Inference Chips The industry is witnessing a shift toward specialized AI inference chips designed to efficiently run AI models in production environments.

Computer Vision: For Robotics and Environmental Awareness

Computer vision technology has advanced to enable robots to interpret and interact with their environments more effectively. Recent developments include AI-driven robotic systems capable of complex tasks such as object recognition, navigation, and real-time decision-making, enhancing automation in various sectors.

Large Language Models (LLMs) & Conversational AI: Chatbots, Assistants, and More

The evolution of LLMs has led to more sophisticated conversational AI systems capable of understanding and generating human-like text. Models like PaLM 2 have demonstrated advanced reasoning capabilities, enabling applications in chatbots, virtual assistants, and other natural language processing tasks.

Spatial Perception: Intelligent Navigation

Advancements in spatial perception technologies have improved the ability of autonomous systems to navigate complex environments. This includes the development of AI algorithms that enable real-time mapping, obstacle detection, and path planning, which are crucial for applications in robotics and autonomous vehicles.

Embedded AIs: Edge Device Integration

Embedded AI involves integrating artificial intelligence capabilities directly into edge devices, allowing for real-time data processing and decision-making without relying on cloud computing. This approach reduces latency, enhances privacy, and enables the deployment of AI in resource-constrained environments.

Industry-Specific AI: Custom AI for Sectors Like Insurance and F&B

Tailored AI solutions are being developed to address specific challenges in various industries. In the insurance sector, AI is used for tasks such as real-time policy issuance and claims assessment. In the food and beverage industry, AI-driven automation systems optimize operations, enhance customer experiences, and improve efficiency.

Distributed Computing: Handling Large-Scale Processes

Distributed computing has become essential for managing large-scale computational tasks across multiple systems. This approach enables efficient processing of big data, supports complex simulations, and facilitates the development of scalable applications, making it a cornerstone of modern computing infrastructure.