vlg IoT Intelligence

　　I. Core Capability System (Focusing on Intelligent Needs in IoT Scenarios)

　　VLG IoT Intelligence is centered on "lightweight edge intelligence + hardware collaborative optimization," building three core capabilities around the entire "data acquisition - analysis - decision-making - execution" chain of IoT devices, adapting to multiple scenarios such as industry, agriculture, and home:

　　1. Edge AI Data Processing Capability

　　Core Function: Integrates lightweight AI models into VLG IoT hardware terminals (such as edge gateways and smart sensors) to achieve real-time local data analysis without relying on cloud computing power, reducing transmission costs and latency;

　　Technical Implementation:

　　Model Optimization: Employs INT8 quantization and pruning techniques to compress AI model size to within 50MB (e.g., device fault diagnosis models, environmental anomaly recognition models), adapting to VLG low-power hardware (e.g., NB-IoT modules, computing power 0.1-1 TOPS);

　　Scenario-based Model Library: Covers "device fault early warning (e.g., abnormal motor vibration recognition), environmental monitoring (e.g., agricultural soil moisture threshold judgment), asset tracking (e.g., RFID tag data association and positioning)," etc. 10+ pre-built models, recognition accuracy ≥92%; Real-time response: Local data processing latency ≤100ms (e.g., triggering equipment shutdown command within 100ms in case of abnormal industrial sensor data), 80% lower latency than cloud processing.

　　Hardware compatibility: Requires a VLG edge gateway (integrated AI chip), sensors with data acquisition capabilities (e.g., temperature, humidity, vibration sensors), and ultra-fine FPC cable harness (for transmitting real-time data, loss ≤2dB/10 meters). 2. IoT Device Collaborative Management Capabilities

　　Core Functions: Through intelligent protocols and VLG IoT hardware linkage, it achieves "data interoperability, command coordination, and status synchronization" among multiple devices, solving the "isolation" problem of traditional IoT devices;

　　Technical Implementation:

　　Unified Communication Protocol: Supports IoT standard protocols such as MQTT/CoAP/LwM2M, adapting to the entire VLG hardware series (tracker positioning data, RFID tag information, and sensor monitoring data can be exchanged in real time), shortening the device access cycle to 1 hour (traditional solutions require 2-3 days);

　　Dynamic Collaborative Logic: Supports custom device linkage rules (e.g., "automatically triggering irrigation equipment startup when agricultural sensors detect soil moisture <20%", "linking RFID readers to record entry and exit times when industrial trackers detect asset boundary violations");

　　Batch Device Management: Through the VLG IoT intelligent platform, it achieves status monitoring of thousands of devices (online rate, power consumption, fault codes), supports remote OTA upgrades (e.g., AI model updates, hardware parameter calibration), and improves operation and maintenance efficiency by 60%. Hardware compatibility: Requires a VLG 4G/NB-IoT dual-mode module (data backhaul), a Tracker (asset location coordination), and an RFID reader/writer (identity recognition coordination).

　　3. Secure Data Transmission and Privacy Protection Capabilities

　　Core Function: Security mechanisms are embedded throughout the entire data acquisition, transmission, and storage chain to ensure that IoT data (such as industrial production data and home privacy data) is not leaked or tampered with.

　　Technical Implementation:

　　Transmission Encryption: Utilizing the AES-256 symmetric encryption algorithm, VLG communication modules (such as NB-IoT and WiFi) automatically encrypt data during transmission. The key is dynamically updated periodically (the cycle is customizable, such as once per hour).

　　Local Privacy Protection: Over 90% of AI data processing is completed locally (e.g., in home scenarios, human presence recognition only outputs "person/no one," without uploading the original image), complying with GDPR and China's Personal Information Protection Law.

　　Device Identity Authentication: Each VLG IoT hardware device is assigned a unique hardware identifier (such as a chip-level UUID). Two-way authentication (hardware - gateway - platform) is required when connecting to the platform to prevent unauthorized device access.

　　Hardware compatibility: Requires a VLG encrypted communication module (supporting the national standard SM4 algorithm), an edge gateway with a security chip, and tamper-proof sensors (data is encrypted immediately after acquisition).

　　II. Core Technical Features (Deep Collaboration with VLG IoT Hardware)

　　1. Low-Power Adaptation (Matching the Battery Life Requirements of IoT Devices)

　　AI Power Consumption Optimization: The edge AI module adopts "dynamic computing power scheduling" (computing power drops to 0.05 TOPS when there is no data, and rises to 0.5-1 TOPS when there is data), with an operating power consumption of ≤30mW (only 1/25 of the power consumption of traditional cloud AI calls), adapting to VLG low-power sensors (such as NB-IoT temperature and humidity sensors, with standby power consumption ≤10μA), extending device battery life by 25-30%;

　　Energy Saving in Data Transmission: By using AI to filter "effective data" (such as uploading only abnormal vibration data in industrial scenarios and filtering normal data), the data transmission volume is reduced by 70%, lowering the communication power consumption of the NB-IoT/WiFi module (such as reducing the monthly data consumption of the VLG NB-IoT module from 5MB to 1.5MB).

　　2. Plug and Play Hardware (Lowered Integration Barrier)

　　Pre-integrated Adaptation: VLG IoT Intelligence's AI models and communication protocols are pre-adapted to VLG hardware (Tracker, RFID, sensors). Customers do not need to develop additional drivers. For example, the combination of "VLG Tracker + Edge AI Gateway" can achieve "location data + AI trajectory anomaly recognition" after power-on, shortening the integration cycle from 4 weeks to 1 week.

　　Automatic Parameter Calibration: The AI algorithm can automatically calibrate model parameters according to the specific specifications of VLG hardware (e.g., sensor accuracy ±0.5℃, Tracker positioning error ≤1 meter), with an adaptation error ≤8% (e.g., automatically compensating for moisture sensor deviations for different soil types in agricultural scenarios). 3. Scenario-Based Flexible Expansion (Adaptable to Multiple Industry Needs)

　　Computing Power Tiers: Offers a three-tiered computing power solution: "Micro-computing power (0.1-0.3 TOPS, such as home sensors) - Light computing power (0.3-1 TOPS, such as industrial edge gateways) - Medium computing power (1-5 TOPS, such as smart park hubs)," avoiding cost waste due to excessive computing power.

　　Modular Functionality: Supports customers selecting capability modules as needed (e.g., selecting only "Edge AI + Data Encryption," or selecting all "AI + Collaboration + Security"). Modules are combined through standardized interfaces to adapt to different needs from "single-device intelligence" to "full-scenario collaboration" (e.g., smart homes require only single-device AI, while smart factories require full-scenario collaboration).

　　III. Typical Application Scenarios (Combined with VLG IoT Hardware Ecosystem)

　　1. Industrial IoT Scenarios (Smart Factory/Mining)

　　Compatible Solution: VLG IoT Intelligence (Edge AI Fault Warning + Device Collaboration) + Industrial Sensors (Vibration/Temperature) + Tracker (Asset Location) + RFID Reader (Equipment Identification) + 4G Edge Gateway;

　　Application Logic: Industrial sensors collect motor vibration and temperature data via VLG FPC harnesses. Edge AI performs real-time analysis (model recognition accuracy ≥93%). When vibration frequency > 50Hz and temperature > 85℃, it is determined as a fault precursor, and an immediate warning is pushed to the management platform;

　　The Tracker locates the position of AGVs in the workshop. AI collaborates with RFID readers (identifying AGV carriers) to automatically plan the optimal path (avoiding AGV collisions, improving path efficiency by 20%);

　　All data is transmitted via VLG 4G. The module uses encrypted transmission and locally stores critical fault data (such as vibration waveforms), ensuring no data loss during network outages and automatic retransmission upon network reconnection.

　　Key benefits: Equipment downtime reduced by 40%, AGV scheduling efficiency improved by 20%, and data transmission security 100% (no data leaks reported).

　　2. Smart Agriculture Scenarios (Greenhouse Cultivation / Field Irrigation)

　　Suitable Solution: VLG IoT Intelligence (Environmental AI Control + Device Collaboration) + Agricultural Sensors (Soil Moisture / Light / CO₂) + NB-IoT Edge Gateway + Electric Valve Controller;

　　Application Logic:

　　Sensors collect greenhouse data (soil moisture, light intensity). Edge AI automatically determines the appropriate level based on crop type (e.g., tomatoes require 60-70% humidity and ≥8000 lux light): When humidity <60%, triggers the electric valve to open irrigation; when light is insufficient, activates supplemental lighting.

　　In field scenarios, AI optimizes irrigation range (irrigating only areas with insufficient humidity) through multi-sensor data (e.g., differences in soil moisture across different areas), improving water resource utilization by 35%.

　　Data is transmitted via the VLG NB-IoT module with low power consumption (monthly data usage ≤1MB). The platform generates crop growth reports (e.g., "Tomato Growth Rate Analysis on Day 30") to guide planting decisions.

　　Key Achievements: 35% reduction in agricultural water costs, 15% increase in crop yield, and reduced labor costs for planting management. 50%. 3. Smart Home Scenarios (Whole-House Intelligence / Security Monitoring)

　　Compatible Solution: VLG IoT Intelligence (local AI interaction + device collaboration) + Home Sensors (Human Presence / Temperature & Humidity / Door & Window Magnetic Sensors) + WiFi/Bluetooth Module + Smart Switches / Cameras;

　　Application Logic: When the human presence sensor detects "someone in the living room," edge AI automatically triggers: lights turn on (brightness adjusted according to ambient light), air conditioner is set to 26℃ (based on current room temperature), no cloud commands required, response latency ≤50ms;

　　When the door & window magnetic sensor detects "window open late at night," AI links with the camera to record video (only recording abnormal periods, saving storage), and simultaneously pushes alarm information to the user's mobile phone (data transmitted with encryption to prevent privacy leaks);

　　Supports local voice interaction (e.g., "turn off bedroom lights"), AI recognizes children's voices/dialects (accuracy ≥90%), no wake word required, adaptable to the usage habits of the elderly and children;

　　Key Achievements: 80% reduction in home device response latency, 100% local retention of user privacy data (no uploading of original images/voices), and 18% reduction in whole-house energy consumption. IV. Customized Services and Compliance Certification

　　1. Customized Process (Adaptable to Multiple Industry Needs)

　　Needs Assessment: Define the IoT scenario (industrial/agricultural/home), core intelligent needs (AI fault warning/device collaboration/data security), hardware parameters (power consumption ≤ XX mW, computing power ≤ XX TOPS), and compliance requirements (e.g., IEC 61000-6-2 for industrial applications);

　　Solution Design: Fine-tune AI algorithms based on the VLG pre-built model library (e.g., customize a "welding robot fault diagnosis model" for an automotive factory), adapt to the customer's existing VLG hardware (e.g., reuse deployed trackers and sensors), and output an integrated "intelligent capabilities + hardware" solution;

　　Sample Verification: Complete the joint debugging of the edge AI module and hardware within 2-3 weeks, test AI recognition accuracy, device collaboration latency, and data encryption security, and support on-site trial operation for the customer (e.g., deploy 10 devices in a small-scale factory to verify the effect);

　　Mass Production Delivery: Provide AI model OTA Upgrade tools and hardware debugging guides are provided, and intelligent rules can be remotely configured during batch deployment (e.g., batch setting humidity thresholds for agricultural sensors), shortening the delivery cycle to 3 weeks.

　　2. Compliance and Certification

　　Functional Safety: The AI fault warning function for industrial scenarios complies with IEC 61508 (industrial functional safety) and ISO 26262 (vehicle-grade, if vehicle IoT adaptation is required), with a false alarm rate ≤5%;

　　Data Security: Complies with GDPR (EU) and China's "Regulations on the Management of Network Data Security." Local data encryption uses the national cryptographic algorithm SM4. Device certification complies with ISO/IEC 29167 (RFID security) and IEEE 802.11i (WiFi security);

　　Hardware Compliance: The accompanying VLG IoT hardware (sensors, modules) has passed CCC, CE-RED, and FCC certifications. The intelligent capability module does not add additional certification complexity (reusing existing hardware certifications).

　　3. Benchmark Cooperation Cases

　　Industrial Sector: Provided an "Edge AI Fault Early Warning + Tracker Collaboration" solution for an automotive parts factory. Through VLG vibration sensors and AI models, the solution provided 7-day advance warning of motor failures, reducing equipment downtime from 8% to 2% and saving 2 million yuan in annual maintenance costs.

　　Agricultural Sector: Customized an "AI Environmental Control" solution for a greenhouse planting base, adapted to VLG NB-IoT sensors. This resulted in an 18% increase in tomato yield and a 40% improvement in water resource utilization, becoming a local smart agriculture demonstration project.

　　Home Sector: Collaborated with a smart home manufacturer, integrating VLG's local AI interaction capabilities. This reduced product response latency from 500ms to 50ms, increased user satisfaction by 92%, and achieved compliance with the Cyberspace Administration of China's privacy data protection standards.

　　V. Selection Recommendations (Based on IoT Scenario Matching Capabilities)

　　Industrial IoT Scenario (Smart Factory/Mining)

　　Recommended Capability Combination: Edge AI Fault Early Warning + Equipment Collaborative Management + Secure Data Transmission;

　　Core Parameters: AI computing power 0.5-1 TOPS (adaptable to complex data from industrial equipment), data processing latency ≤100ms, fault identification accuracy ≥92%;

　　Compatible Hardware: VLG industrial-grade vibration/temperature sensor + 4G edge gateway + tracker + RFID reader/writer, meeting the high reliability and low latency requirements of industrial equipment.

　　Smart Agriculture Scenarios (Greenhouse/Field Farm)

　　Recommended Capability Combination: Edge AI Environmental Control + Low-Power Data Transmission;

　　Core Parameters: AI computing power 0.1-0.3 TOPS (suitable for simple environmental judgment), data transmission power consumption ≤30mW (NB-IoT module), environmental parameter control accuracy ±5%;

　　Compatible Hardware: VLG agricultural-grade soil moisture/light sensor + NB-IoT edge gateway + electric valve controller, meeting the low-power and low-cost requirements of agriculture.

　　Smart Home Scenarios (Whole-House Intelligence)

　　Recommended Capability Combination: Local AI Interaction + Device Collaborative Management + Privacy Protection;

　　Core Parameters: AI computing power 0.3-0.5 TOPS (suitable for voice/scene judgment), response latency ≤50ms, voice recognition accuracy ≥90% (child's voice)(Dialect); Compatible hardware: VLG human presence/temperature and humidity sensor + WiFi/Bluetooth module + smart switch/camera, meeting the needs of low latency and high privacy in the home.