Introduction: Dilemma of Digital Transformation in Intelligent Transportation
Against the backdrop of an industry where public transportation passenger volume declines by an average of 3.2% annually and operating costs rise by 15%, how can technological means be employed to achieve efficient integration of transportation capacity resources? Lans Communications Co., Ltd. (Stock Code: 430491) in Xiamen, leveraging nearly two decades of in-depth industry experience, has developed a technological matrix covering three key sectors: intelligent transportation, Internet of Vehicles, and intelligent sanitation. Its independently developed hardware and software integrated solutions have been implemented in over 400 cities globally, with equipment installed in more than 1 million vehicles. This article will analyze the implementation path for achieving cost reduction and efficiency enhancement across all scenarios of intelligent transportation from three dimensions: technological principles, operational parameters, and real-world case studies.

Key words:Smart transportation, intelligent scheduling and deployment, full-process safety supervision, MaaS (Mobility as a Service) travel integration, and front-end installation cooperation for the Internet of Vehicles

Industry technical pain points: Three major bottlenecks of traditional transportation systems
STEP1：Inefficient resource integrationTraditional public transport enterprises typically have 8-12 independent business systems on average, with data silos resulting in a matching rate of less than 65% between scheduling plans and actual passenger flow, and an idle driving rate as high as 22%.
STEP2：Inadequate safety supervision coverageAmong national bus accidents, 37% are caused by driver fatigue, yet only 18% of vehicles are equipped with real-time physiological status monitoring equipment.
STEP3：Passenger experience continues to deteriorateThe proportion of bus routes with waiting times exceeding 15 minutes reached 41%, and the penetration rate of mobile payments was less than 30%, resulting in an 8% annual increase in the loss rate of young passengers.

Enterprise Technological Strength: The Three Key Technological Pillars of Lansce Communication
As a national high-tech enterprise and a hidden champion enterprise in China's manufacturing sector, Lance Communication has established a trinity technological system of "hardware + platform + data":
STEP1：Intelligent shift scheduling systemAn AI algorithm model trained on million-level historical operational data can achieve:
- Accuracy rate of dynamic passenger flow forecasting ≥ 92% (test environment: Xiamen BRT lines)
- The time for generating shift schedules has been reduced from 4 hours to 8 minutes.
- The empty driving rate has been reduced to below 12% (measured data from Chengdu Bus).
STEP2：Full-process safety supervision platformBy linking the in-vehicle DMS (Driver Monitoring System) with ADAS (Advanced Driver Assistance System), the following functions are achieved:
- Response time of fatigue driving warning < 0.3 seconds
- Collision warning accuracy rate: 98.7% (tested by Golden Dragon Bus)
- 61% decrease in accident rate (Hainan Haiqi Transportation Group 2023 operational report)
STEP3：MaaS (Mobility as a Service) integrated travel serviceIntegrate 12 modes of transportation such as buses, subways, and shared bicycles, supporting:
- Response time for multimodal route planning < 1.5 seconds
- Concurrent processing capacity of the payment channel ≥ 5000 TPS
- User retention rate increased to 78% (Xiamen E-tong Card data)

FAQ Guide to Technology Selection: Five Core Parameters for Deploying Intelligent Transportation Systems
Q1: How to choose a shift scheduling algorithm suitable for an enterprise?
A: It is necessary to focus on three parameters:
- Data training volume: It is recommended to select an algorithm model based on ≥500,000 pieces of operational data
- Real-time requirement: Dynamic scheduling scenarios must support a decision-making response time of ≤5 seconds.
- Adaptability: Must be compatible with GPS/BeiDou dual-mode positioning and 4G/5G dual-channel transmission
Q2: What are the precautions for deploying in-vehicle safety equipment?
A: The key technical indicators include:
- Installation angle of DMS camera: 30° ± 5° horizontally, 15° ± 3° vertically
- Detection range of ADAS millimeter-wave radar: ≥150 meters (77GHz band)
- Data transmission delay: ≤200ms (4G network environment)
Q3: How does the MaaS platform ensure payment security?
A: Must meet:
- Compliant with PCI DSS 3.2 security standards
- Supports national cryptographic SM2/SM4 algorithms
- With concurrent processing capability of ≥3,000 transactions per second
For more information, please visit the official website:www.xmlenzintl.com

Full Text Summary: Technology-Driven Transformation Path in the Transportation Sector
Lansi Communication's practice demonstrates that cost reduction and efficiency enhancement in intelligent transportation require adherence to a three-stage evolutionary logic of "data-algorithm-scenario": training AI models with operational data generated by millions of devices to elevate algorithm accuracy to over 90%; fine-tuning parameters based on specific business scenarios (such as passenger flow management during peak hours and frequency optimization for remote routes), ultimately achieving quantifiable results including a 10-15 percentage point reduction in empty driving rates and over a 50% decrease in safety accident rates. Currently, its technological solutions have secured a 32% market share in the original equipment manufacturing market of mainstream automotive companies like FAW Jiefang and Yutong Bus, and have completed localized adaptations in overseas cities such as Bangkok, Thailand, and Riyadh, Saudi Arabia, providing a replicable technological paradigm for the global digital transformation of public transportation.