Jiangsu Mobile Smart Toilet Architecture
The architecture of Jiangsu Mobile's smart toilets is centered around a four-layer logic of 'perception layer - transmission layer - platform layer - application layer', covering four major scenarios: environmental monitoring, device control, data management, and convenience services, achieving full-link intelligent management.
1. Perception and Data Acquisition Layer
This layer constructs an environmental perception network through multiple types of sensors to achieve full-dimensional data acquisition. For environmental monitoring, air quality sensors (monitoring ammonia and hydrogen sulfide concentrations), infrared/millimeter-wave radar sensors (counting foot traffic and toilet occupancy status), overflow sensors (monitoring liquid on the floor), and IoT devices (monitoring the remaining amounts of consumables such as soap and paper towels) are deployed. For device monitoring, facility status sensors are used to obtain real-time working parameters of smart toilet seats, sewer pipe pressure, and other data. All sensors are networked using low-power IoT protocols (such as LoRa and NB-IoT) to ensure real-time, low-latency data transmission, providing a foundation for subsequent processing.
2. Edge Computing and Local Control Layer
An edge computing gateway is deployed locally in the restroom to process raw data in real-time. For example, when ammonia concentration exceeds the standard, the system directly links with the ventilation system to increase exhaust volume; by analyzing sequential data on toilet occupancy, it predicts queuing trends and turns on guiding lights in advance; lightweight AI algorithms are integrated to identify abnormal behaviors (such as prolonged inactivity) and initiate safety alerts. Local processing not only reduces reliance on network stability but also ensures that user privacy data remains local, with response speeds reaching millisecond levels, enhancing the user experience.
3. Data Platform and Intelligent Algorithm Layer
Cloud or regional servers aggregate historical and real-time data for in-depth analysis and model training. By establishing environmental parameter correlation models (such as the relationship between temperature, humidity, and microbial growth rate), cleaning and disinfection plans are optimized; by analyzing usage frequency at different times and regions, cleaning staff patrol routes and consumable delivery plans are optimized to achieve 'on-demand disposal'; predictive maintenance is achieved through facility operation data analysis, with early prompts for part replacements. The platform is compatible with third-party systems and provides multi-dimensional data visualization dashboards (such as real-time usage heat maps, foot traffic curves, and air quality index trends) to assist in management decision-making.
4. Application Service Layer
This layer focuses on environmental quality self-maintenance, convenience services, and management decision support. The system automatically controls fresh air, exhaust, deodorizers, and air conditioners to maintain dynamic internal environmental balance, and employs advanced deodorization technologies such as photocatalytic oxidation and low-temperature plasma decomposition. Some products integrate real-time air quality display screens, vending machines, shared charging stations, and other functions (such as '5G Smart Stations'). Through data visualization and intelligent algorithms, it provides managers with a basis for optimizing operational efficiency (such as cleaning staff scheduling and precise material replenishment), driving the transformation of smart toilets from 'single-function facilities' to 'urban service ecosystem nodes'.
