Towards proactive maintenance of buried infrastructure with cloud-based sensing and predictive analytics

地下基础设施的状况，包括水、废水和雨水管网，对人们的生活质量非常重要，并具有强烈的环境、经济和社会影响。最近在加拿大进行的一项市政地埋基础设施调查发现，水污染、安全和供水系统状况是这个国家面临的最大问题。城市漏水浪费了数百万纳税人的钱。公用事业公司主要通过响应式方法来解决这些问题。需要一种基于性能的方法来确定单个供水管道是否满足所需的服务水平。然而，由于技术和资金的限制，这些隐藏资产的绩效管理一直没有实施。主动、统一和系统的方法来维护埋在地下的基础设施将更有效和更可取。******为了实现对埋地基础设施的主动维护，从管道中收集所有相关数据和信息以确定未来管道状况至关重要。目前，现场监测和无损检测是收集数据的主要方法。然而，这些数据以不同的格式保存并存储在不同的地方。由于这些数据之间没有正确匹配和对齐，因此只能使用孤立的数据构建预测模型。基于累积检测数据的综合预测可用于开发下一代主动维护。该研究项目将通过将物联网、云计算、先进机器学习等现代信息和通信技术融入到埋藏的基础设施管理中，填补技术空白。******该研究项目的长期目标是推进状态评估技术和预测分析，通过主动维护实现地下基础设施的可持续性。短期内，该研究计划将开发基于云的传感框架，该框架将实现集中数据收集、存储和管理，并开发预测分析，从大检测数据中获得可操作的信息。******主动维护允许自来水公司采取正确有效的预防和纠正措施。因此，对加拿大地下基础设施带来的影响包括更高的系统可靠性，降低管道故障成本，减少维护时间，优化维护间隔。拟议的研究也将为HQP提供一个独特的跨学科培训机会。HQP将获得多个学科的深入知识和理解，例如电气，土木和机械工程，并能够解决实际问题，而不考虑学科界限。

The condition of buried infrastructure including water, wastewater, and storm water networks is of great importance to people's quality of life and has strong environmental, economic and social implications. A recent municipal buried infrastructure survey across Canada identified water pollution, safety and state of water supply systems as the greatest issues to this country. City water leaks are wasting millions of tax dollars. Utilities are addressing these issues primarily with a reactive approach. A performance-based approach is needed to identify if individual water pipelines meet the required level of service. However, performance-based management of these buried assets has historically not been performed due to technical and financial limitations. A proactive, uniform, and systematic approach for maintenance of buried infrastructure would be more efficient and preferred.******To achieve the proactive maintenance of buried infrastructure, it is essential to collect all the relevant data and information from the pipelines to determine future pipe condition. Currently, in-situ monitoring as well as non-destructive inspection are performed to collect the data. However, these data are saved in different formats and stored in varied places. As these data are not properly matched and aligned to each other, predictive models can only be built with isolated data. A comprehensive prediction based on accumulated inspection data can be used to develop next-generation proactive maintenance. This research program will fill the technical gaps by incorporating modern information and communications technologies, e.g. Internet of Things, cloud computing, and advanced machine learning, into the buried infrastructure management. ******The long-term objective of the research program is to advance condition assessment technologies and predictive analytics to achieve the sustainability of buried infrastructure through proactive maintenance. In the short-term, the research program will develop a cloud-based sensing framework, which will enable centralized data collection, storage, and management, and develop predictive analytics to derive actionable information from big inspection data. ******Proactive maintenance allows preventive and corrective actions from water utilities to be properly and efficiently scheduled. Thus, the impacts brought to Canada's buried infrastructure include higher system reliability, reduced costs of pipe failures, minimized time on maintenance, and optimized maintenance interval. The proposed research will also offer a unique cross-disciplinary training opportunity for HQP. The HQP will gain in-depth knowledge and understanding of more than one discipline, e.g. electrical, civil, and mechanical engineering, and be able to solve practical problems without regard to disciplinary boundaries.