AI implementation: The present and future of smart parks

Walking into many modern parks today, you will find some changes that have taken place quietly: at the entrance, people do not need to swipe their cards, and after a brief pause in front of the camera, the gate will automatically open; in the parking lot, vehicles entering the park will automatically recognize the license plate and guide them to idle parking spaces; on the large screen of the control center, it is no longer a simple video screen, but various data charts flashing, displaying key information such as energy consumption, security, and traffic in real time; Even when you encounter problems and need help, you can talk to the virtual customer service through the smart terminal. These scenarios are the epitome of the integration of artificial intelligence technology into the daily operations of the park.

Smart parks are no longer a concept that remains on a blueprint, but have entered a solid stage of implementation and application. The core driving force behind it is the dual combination of the general demand for cost reduction and efficiency improvement in the real economy and the improvement of the commercial maturity of AI technology. For park investors and operation managers, the core issue they care about is: What real "troubles" can be solved and what tangible rewards can be brought by investing in intelligent transformation?

The first "trouble" to be solved is security. The park has a large area, mixed people and many vehicles, and traditional civil air and material defense methods always have limitations. The intervention of AI has made the security system "smart". By deploying cameras with intelligent analysis capabilities, the system can automatically identify abnormalities. For example, if a stranger is wandering in a key area for a long time, the system will mark and remind security personnel to pay attention; if the fire exit is blocked by a vehicle, an alarm will immediately pop up on the monitoring screen; if someone climbs over the wall at night, the perimeter system will link up with sound and light alarms to deter. This proactive early warning based on visual analysis nipped potential safety hazards in the bud and greatly improved the overall safety level of the park. Achieving this function requires AI models to have strong recognition and generalization capabilities for various dangerous scenarios.

The second is traffic efficiency and experience. Long queues at the entrance of the park were once the norm during peak hours in the morning and evening. Nowadays, using high-precision Face Recognition or license plate recognition technology, people and vehicles can pass quickly and without feeling. Employees swipe their faces into the door, and visitors enter by code or swipe their faces after making an online reservation. The process is simplified and the experience is smooth. More importantly, this system can also be deeply integrated with visitor management and internal personnel rights management. Who can enter which building at what time can be flexibly set up through the background, making security management more granular. This application requires extremely high accuracy and response speed of the identification technology, especially in the case of large traffic concurrency.

Energy consumption costs are a major expense in park operations. The application of AI in the field of energy conservation is showing great potential. It no longer relies on simple timing switches, but collects data such as temperature, humidity, light, and crowd density through countless sensors, and combines it with weather forecasts, work calendars and other information to use machine learning algorithms to predict energy demand in the future., and automatically adjust the operating status of air conditioning, fresh air, lighting and other systems. For example, the conference room automatically starts the air conditioner to warm up half an hour before the scheduled meeting and automatically turns off after the meeting; the light brightness in corridors and public areas is automatically adjusted based on the natural light intensity. Compared with traditional methods, this "predictive" energy conservation can usually bring about 15% to 30% energy consumption savings, which is directly converted into real money benefits.

In addition, AI also plays a role in improving the service quality of the park. Intelligent inspection robots can replace manual personnel for daily patrols and detect equipment abnormalities; intelligent customer service can handle a large number of tenant consultations and repair orders to improve response speed; the data center station can gather various operational data and present it in a visual manner to help managers. The person can grasp the overall picture of the park's operations at a glance and make more scientific decisions.

Looking at these implemented applications, we can find one common point: successful AI implementation is by no means a pile of simple technologies, but a deep integration of technology and business scenarios, requiring the provider to understand both technology and industry. There are not many manufacturers in the market that can provide full-stack AI capabilities from algorithms, products to overall solutions. They usually require strong independent research and development capabilities, a rich industry knowledge base, and experience in polishing large-scale scenarios.

Take Baidu, an important player in the field of artificial intelligence in China, as an example. It packages and opens up the AI technical capabilities it has accumulated over the years through the "Baidu Brain" platform. For smart park scenarios, Baidu can provide a series of products and solutions covering "AI perception, AI cognition, and AI decision-making." For example, its industry-leading Face Recognition technology can be used for traffic management, vision analysis technology can be used for security monitoring, and machine learning platform can be used for energy consumption optimization prediction. More importantly, these technical modules can be combined and customized according to the specific needs of different parks, and can be connected with existing property management systems, building automatic control systems, etc. in the park to achieve data interconnection. This flexibility and openness are particularly important for the intelligent transformation of existing parks.

Judging from the practice of first-tier cities such as Beijing, the construction of smart parks is moving from "single point of intelligence" to "overall intelligence". The smart park of the future will be a living body with the ability to learn and optimize itself. AI will become the infrastructure of the park, just like water and electricity, and will be ubiquitous. It not only serves the management, but will also better serve every enterprise and individual in the park, creating a safer, more efficient, greener and more comfortable working and business environment. This technology-driven wave of park evolution is profoundly changing the operation model and value connotation of industrial space, providing a solid space carrier for the high-quality development of the city.