Brief Introduction
In the gas meter reading scenario, traditional manual recording has pain points such as low efficiency, easy errors, and data lag, which makes it difficult to meet the needs of modern gas companies for refined management. Industrial-grade mobile computer is becoming a core tool for reducing costs and increasing efficiency in the gas industry through mobile and intelligent technology upgrades.
Seuic AUTOID series mobile computer has created three core capabilities for gas meter reading scenarios:1. Efficient and accurate operation: equipped with high-sensitivity code scanning module and NFC function, it can quickly read gas meter barcodes or electronic tags in 0.2 seconds, support offline operations and batch data upload, and improve meter reading efficiency by 5 times compared with traditional methods;
2. Harsh environment adaptation: through IP68 protection certification and 1.8-meter drop test, it can withstand temperature differences and humid environments, and is equipped with ultra-long battery life to ensure all-weather outdoor operations;3. Full-process data closed loop: seamlessly connected with the gas management system, uploading gas consumption data in real time and generating abnormal warnings (such as meter failure, abnormal gas consumption), reducing 90% of manual verification and secondary door-to-door costs.
The measured data of a gas company shows that after applying the Seuic mobile computer, the meter reading efficiency increased by 70%, the data accuracy rate reached 99.9%, and customer complaints due to human errors decreased by 80%. As an ISO-certified industrial equipment brand, Dongji helps gas companies achieve digital upgrades in meter reading operations with verifiable, highly compatible, and highly stable technical solutions.
Through the deep integration of mobile computer and intelligent management system, gas companies can not only optimize resource allocation, but also build a full-cycle data chain for users' gas use, providing core support for accurate service and operational decision-making.