--- title: "Track Hyper | GMTECH strengthens its layout in home-based elderly care" type: "News" locale: "en" url: "https://longbridge.com/en/news/247372463.md" description: "Launched a dedicated AI intelligent body, but still faces challenges in technological breakthroughs and real-world dilemmas" datetime: "2025-07-05T08:56:26.000Z" locales: - [zh-CN](https://longbridge.com/zh-CN/news/247372463.md) - [en](https://longbridge.com/en/news/247372463.md) - [zh-HK](https://longbridge.com/zh-HK/news/247372463.md) generator: "portal-rs" --- # Track Hyper | GMTECH strengthens its layout in home-based elderly care Author: Zhou Yuan / Wall Street News At the end of June, GMTECH launched the country's first AI smart assistant specifically for home-based elderly care, marking a proactive exploration by technology companies into the transformation of elderly care services. However, the gap between technological ideals and reality has always existed, and this product is facing multiple challenges in its implementation process, from technical architecture to market adaptation. The AI smart assistant from GMTECH adopts a multi-agent model, drawing on the classic theory of distributed artificial intelligence—breaking down complex tasks into multiple sub-tasks, which are executed independently by different agents. This architecture has been proven to enhance system response speed and processing efficiency in laboratory environments, but in the context of home-based elderly care, the challenges of real-world scenarios are difficult to effectively change. From the perspective of data collection, the complexity of the home environment far exceeds expectations. Taking the health monitoring module as an example, data such as the range of motion of elderly individuals while cooking in the kitchen and the frequency of nighttime bathroom visits need to be collected collaboratively through multiple sensors (such as cameras, pressure-sensitive mats, and wearable devices). However, there are differences in data formats and sampling frequencies among different sensors, and achieving unified labeling and fusion analysis of multi-source heterogeneous data remains a challenge that has not been fully conquered in the current field of artificial intelligence. Research from Stanford University's Artificial Intelligence Laboratory indicates that in complex scenarios, for every 1% increase in the accuracy of multi-source data fusion, the algorithm's complexity will grow exponentially. This confirms the viewpoint of mathematician Claude Shannon: information is used to eliminate randomness, but in the pursuit of information accuracy, the complexity of technology is also continuously rising. In terms of implementing a collaborative cognitive model, the combination of edge computing and large models seems advanced, but it actually faces a contradiction between computing power and energy consumption. Home-based elderly care devices typically use low-power chips to extend battery life, but this limits the real-time operation of complex algorithms. Currently, there is no evidence to suggest how GMTECH will address this issue. The industry typically employs a strategy of "local preprocessing + cloud deep analysis" for data, but delays in data transmission (even 5G networks have millisecond-level delays) can lead to lag in emergency response. Norbert Wiener, the founder of cybernetics, warned in his seminal work "The Human Use of Human Beings: Cybernetics and Society" that "the development of technology must be coordinated with human needs and safety," and this contradiction is an obstacle that must be overcome when technology adapts to real-world demands. What is even more concerning is the disconnection between technology and user habits. Although natural language processing technology can facilitate smooth conversations, elderly individuals often mix dialects and vague expressions in their language habits, and there may even be communication difficulties due to hearing impairments. This requires technology to more accurately identify these issues and provide precise solutions, which currently lacks suitable solutions in the industry. The core demands of home-based elderly care are the dual satisfaction of life assistance and emotional comfort. Although GMTECH's AI smart assistant covers scenarios such as health monitoring and life services, there remains a significant gap between the technological functions of the industry chain and human needs in practical applications. GMTECH has not explained how they will improve this gap between technology and demand. From a commercial perspective, the monitoring functions in the health and safety field can indeed fill some gaps in care Through mattress sensors to record sleep quality and smart wristbands to track heart rate changes, data can provide remote care references for children. However, the technological limitations are significant: it can only monitor physiological indicators and cannot perceive psychological states. Many elderly individuals are in a "silent" state and are not detected in a timely manner. Mental health issues among the elderly are often hidden in daily behavioral details, such as reduced social frequency and loss of enthusiasm for hobbies. The existing smart devices have very limited capabilities in capturing such non-physiological data, indicating that technology still has a long way to go in meeting higher-level human needs. Virtual social interactions cannot replace real interactions. Online interest groups and smart chatbots can provide companionship, but they lack non-verbal information such as eye contact and body language found in real social interactions. The risk of data privacy protection cannot be ignored. Smart devices optimize services by analyzing user conversations, which inevitably involves collecting sensitive information about the elderly's living habits and family relationships. The EU's General Data Protection Regulation (GDPR) requires explicit authorization for processing personal health data, but the digital literacy of the elderly population is generally low, making them prone to the "consent trap." The lack of industry standards has led to market chaos. Currently, the performance indicators and safety standards for smart elderly care devices have not been unified, resulting in uneven product quality. In the fall detection device market, some products are overly sensitive and will trigger alarms even when the elderly simply get up; others are slow to respond and do not react when a real fall occurs. This chaotic market situation severely affects consumer confidence in smart elderly care devices and highlights the urgency of establishing unified industry standards, which cannot be achieved by a single company alone. Without unified standards, companies lack clear references for product development, making it difficult for consumers to judge product quality, which is detrimental to the overall healthy development of the industry. The development of smart elderly care requires collaboration among enterprises, government, and society to find a balance between technological innovation and humanistic care, truly realizing the industrial vision of "technology for good." In 2024, GMTECH achieved a total operating revenue of 549 million yuan, a year-on-year increase of 3.15%; net profit attributable to shareholders reached 169 million yuan, a year-on-year increase of 61.41%, setting a new historical high; net profit reached 169 million yuan, a year-on-year increase of 61.41%, marking the best performance since the company's establishment. In 2024, GMTECH's first large-scale Internet of Things experimental community for simulated home elderly care, "GMTECH University Elderly Care," will be officially promoted. This experimental community aims to improve overall operational efficiency and quality by integrating Internet of Things technology with university elderly care, providing users with a more vibrant and spiritually fulfilling elderly care experience. Since its initial promotion, the market response has been enthusiastic, with platform exposure exceeding one million, but there is still a lack of disclosure regarding actual operational effects and profitability. The release of a dedicated AI smart device for home elderly care by GMTECH is undoubtedly a positive exploration, providing ideas for the digitalization of elderly care, but there is still a long way to go before mature applications are realized ### Related Stocks - [002093.CN](https://longbridge.com/en/quote/002093.CN.md) ## Related News & Research - [Trump’s Bond Buyback Push Puts Kevin Warsh in a Tough Spot — Peter Schiff Says Treasury ‘Pulled the Rug Out From Under’](https://longbridge.com/en/news/296615127.md) - [REG - CQS Natural Res - Sale of Shares from Treasury](https://longbridge.com/en/news/296512957.md) - [S99 PR Announces Signal Press Framework as AI Search Reshapes Brand Discoverability](https://longbridge.com/en/news/296616980.md) - [REG - Cerillion PLC - TR-1 Notification](https://longbridge.com/en/news/296370992.md) - [SpareBank 1 Østlandet employee share buyback offer book closes Aug. 20 at 16:00 CEST](https://longbridge.com/en/news/296449504.md) --- > **Disclaimer: This article is for reference only and does not constitute any investment advice.**