With the global digital binoculars market expanding at a compound annual growth rate (CR) of 14.2% (2023-2025 data), demand is clearly stratified between consumer-grade (birdwatching, outdoor) and professional-grade (scientific research, security) segments. Camera module manufacturers must build product matrices "oriented by demand" and seize growth opportunities in this emerging market through upstream and downstream supply chain collaboration.
I. Module Product Strategies Under Stratified Market Demand
- Consumer-Grade Market: Adaptation of Low-Cost, Cost-Effective Modules
Consumer-grade products (e.g., Solvia ED 8x32 with a crowdfunding price of $269-$349) focus on "cost control + basic function satisfaction," with core requirements for modules including:
- Resolution: 8MP (1/2.7-inch CMOS) is sufficient for 2880×2160 video recording, without the need for high pixels (to avoid cost increases);
- Lens configuration: 4P plastic lenses (light transmittance ≥80%), reducing costs by 30% compared to 5P/6P lenses, while compensating for image quality gaps through software algorithms (e.g., AI noise reduction);
- Function integration: Only retain "basic ISP + Wi-Fi transmission" modules, omitting high-end configurations such as NPUs (AI recognition relies on the cloud or mobile APP to reduce module complexity).
In response, we need to build a "standardized consumer-grade module platform," controlling module costs between $15-$20 through large-scale production (single-batch capacity ≥100,000 units) to adapt to the pricing strategy of crowdfunding products.
- Professional-Grade Market: Breakthroughs in High-Specification, Customized Modules
Professional-grade products focus on "high-precision recognition + durability," with significantly upgraded requirements for modules:
- Resolution and light sensitivity: CMOS with 13MP or higher (e.g., Sony IMX586) featuring a 1/1.7-inch large sensor to improve low-light image signal-to-noise ratio (≥45dB);
- Function integration: Embedded NPU (e.g., Huawei Ascend mini NPU) supporting local recognition of over 9,000 bird species (recognition accuracy ≥90%) without relying on the cloud;
- Protection level: IP67 dust and water resistance (higher than consumer-grade IP64), with modules adopting stainless steel casings + fluororubber sealing to withstand long-term humid outdoor environments.
For such needs, we need to establish a "customized R&D team" and intervene in downstream manufacturers' product design 6-8 months in advance. For example, customize a lens group with an 11° field of view based on the AX Visio's "10x magnification + 32mm objective lens" parameters to ensure full matching between the recognition area and the observation area.
II. Supply Chain Collaboration: From "Passive Supporting" to "Active Co-Creation"
- Collaborative Customization of Core Upstream Components
Key components of smart binoculars modules (CMOS, lenses, sealing materials) require differentiated selection, necessitating in-depth collaboration with upstream manufacturers:
- CMOS layer: Jointly develop "low-power, high-sensitivity models" with domestic manufacturers (e.g., SmartSens, OmniVision). For example, target outdoor battery life requirements by reducing the CMOS's "sleep power consumption" to below 2mA (conventional models are 5mA), while improving low-light sensitivity through pixel binning technology (4-in-1);
- Lens layer: Collaborate with Sunny Optical and Largan Precision to develop dedicated lenses with "ED glass + anti-fog coating," addressing chromatic aberration superposition between the binoculars' optical system and the module lens (controlling total chromatic aberration within 0.5λ);
- Sealing material layer: Customize weather-resistant sealants with 3M to ensure the module maintains IP64 protection performance after 1,000 cycles of -40℃~85℃ testing (conventional sealants are prone to aging and failure above 50℃).
- Joint R&D Mechanisms with Downstream Manufacturers
Traditional camera module business mostly follows a "downstream provides parameters, we produce to specifications" model, but smart binoculars require "optical-electronic-algorithm" collaboration, necessitating a shift to a "joint R&D" model:
- Early stage: Participate in the design of downstream manufacturers' optical systems. For example, for the TrueFrame™ system of the Solvia ED 8x32, provide the module's "optical path deviation tolerance" (≤0.05mm) to help optimize the prism position;
- Mid-term: Jointly conduct reliability testing, such as simulating outdoor scenarios like "sudden temperature changes (-10℃→30℃) and dust impact" to verify the module's imaging stability (image clarity attenuation ≤5% after 1,000 consecutive tests);
- Late stage: Synchronously iterate firmware, such as optimizing the module's "AI recognition algorithm" based on user feedback to improve bird recognition accuracy under backlighting (from 85% to 92%).
- Ecological Collaboration Expansion
The "sharing function" of smart binoculars requires the module to be compatible with APPs and cloud data platforms, requiring ecological collaboration expansion:
- Collaborate with APP developers to optimize the module's image output format (e.g., dual output of RAW + JPEG) to facilitate AI enhancement by the APP (e.g., Solvia's "AI deblurring" function);
- Collaborate with geographic information service providers (e.g., Amap) to integrate lightweight GPS modules (e.g., Beidou-3 microchips) into the module, enabling automatic geotagging of captured images (error ≤10 meters) to meet the demand for "birdwatching log generation."
III. Future Development Direction: From "Function Supporting" to "Value Empowerment"
- Scenario Extension: From Consumer-Grade to Professional Fields
As smart binoculars extend to security and military fields (e.g., border patrol, wildlife protection), modules need to upgrade to "high resolution + encrypted transmission":
- Security field: Develop 20MP modules supporting 4K@60fps video recording, while integrating hardware encryption chips (e.g., national secret SM4 algorithm) to prevent data leakage during transmission;
- Military field: Modules must have "electromagnetic interference resistance," adopting shield covers + filter capacitors to maintain normal imaging in strong electromagnetic environments (e.g., radar radiation areas).
- Cost Optimization: Promoting Popularization of the Consumer-Grade Market
Currently, the camera module accounts for approximately 15% of the BOM cost of consumer-grade smart binoculars (the total BOM cost of the Solvia is about 27). Cost reduction through large-scale production and localization is required:
Large-scale production: When annual sales of consumer-grade products exceed 500,000 units, large-scale module production can reduce costs to $12- $15 (a 40% decrease);
- Localization: Increase the localization rate of core components (CMOS, NPU) from the current 30% to 80%, further reducing the cost premium from relying on imports (e.g., domestic CMOS is 20% cheaper than similar Sony products).
As camera module manufacturers, our core competitiveness is no longer "production scale" but "technical adaptation capabilities for segmented scenarios" and "supply chain collaboration efficiency." In the smart binoculars market, only by accurately grasping the core needs of "optical coordination, environmental adaptation, and function integration" can we upgrade from "supporting suppliers" to "value co-creation partners" and take the initiative in a market growing at 14.2%.
