A service for global water level and river flow data based on pervasive sensor networks

基于普适传感器网络的全球水位和河流流量数据服务

• 批准号: NE/S009051/1
• 负责人: Wouter Buytaert
• 金额: $ 1.33万
• 依托单位: Imperial College London
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2018
• 资助国家: 英国
• 起止时间: 2018 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=NE%2FS009051%2F1
• 关键词: service; global; water; level; river; service; global; water; level; river

Floods and droughts are among the most damaging and disruptive natural hazards worldwide. The development of adaptation and mitigation strategies such as flood forecasting systems relies on accurate observations of water level and river flow. However, the world's rivers are still very poorly monitored and existing monitoring networks are often very sparse in space and time. This is a major bottleneck for water resources management and risk reduction.We have developed a "smart" sensor network that consists of a combination of novel, low-cost sensor technologies and computer algorithms to manage the network. With this network we can monitor and derive various river flow parameters in a way that is far more cost-effective, robust, flexible, and environmentally friendly than existing methods.We have applied our technologies around the world and in a wide variety of applications, including groundwater well monitoring in Somalia, evaluating green infrastructure for water security in Peru, and supporting community-based flood early warning in Nepal. These applications have allowed us to test and refine the performance and robustness of the technology in real-world conditions, and has also exposed the technology to potential end-users. This has generated a broad interest, including various specific requests to purchase the sensors and related technologies.Based on this experience, we see an opportunity to commercialize our technology by building an innovative global service for application-tailored water level and river flow data and analytics. Before applying for an Innovation Follow-On award, we intend to implement a set of activities to formalize our end-user engagement and analyse the potential market. This will allow us to understand end-user needs, and to identify an appropriate business model for the service. Through the Imperial College MBA Connect programme, we have teamed up with the Imperial Business School student Henry Spethmann. Before embarking on MBA studies at Imperial College, Henry has been involved in several technology start-ups in Europe and the United States. As a result, he has extensive expertise on market analysis and business model development, which is highly complementary to the technological and scientific expertise of Dr Buytaert's group.We intend to use the Pathfinder funding to contract Henry to develop a strategy for end-user engagement that will provide us with the necessary input in the development of the business model. Through our previous interactions and experience, we identified a set of potential clients (see section on "Beneficiaries" for more details). However, their requirements are diverse and suggest different potential business models, ranging from selling sensors to providing a set of services related to installation, operation, and data analysis. Therefore, we aim to conduct interviews with potential customers to understand the business context in which they operate, e.g. current needs, most difficult areas of operation, how much monitoring is already in place, and proportion of total budget allocated for hydrological data generation. This information will allow us to identify one or more suitable business models, as a first step towards the development of a business plan.In conjunction to the end-user interaction and business model development, we also aim to explore the intellectual property context, implement a risk analysis, and identify relevant competitors.

洪水和干旱是全球最具破坏性和破坏性的自然危害之一。适应和缓解策略（例如洪水预测系统）的发展取决于对水位和河流流量的准确观察。但是，世界河流的监测仍然很差，现有的监测网络在时空通常非常稀少。这是用于水资源管理和降低风险的主要瓶颈。我们开发了一个“智能”传感器网络，该网络由新颖的低成本传感器技术和计算机算法组成，用于管理网络。使用该网络，我们可以以比现有方法更具成本效益，健壮，灵活和环保的方式监视和得出各种河流流参数。我们已经在世界范围内应用了我们的技术以及各种应用，包括索马里的地下水井监测，在秘鲁和基于社区的洪水泛滥的洪水泛滥中，评估了绿色的绿色基础设施，并评估了NEP的水上供应。这些应用程序使我们能够在现实世界中测试和完善技术的性能和鲁棒性，并将技术暴露于潜在的最终用户。这引起了广泛的兴趣，包括购买传感器和相关技术的各种特定要求。根据这一经验，我们看到了一个机会，通过建立创新的全球水平服务，用于应用程序销量的水位以及河流流量数据和分析。在申请创新后续奖励之前，我们打算实施一系列活动，以正式化我们的最终用户参与并分析潜在市场。这将使我们能够了解最终用户的需求，并确定服务的适当业务模型。通过帝国大学MBA连接计划，我们与帝国商学院的学生亨利·斯佩特曼（Henry Spethmann）合作。在帝国大学开始MBA研究之前，亨利曾参与欧洲和美国的多家技术初创企业。结果，他在市场分析和业务模型开发方面具有广泛的专业知识，这与Buytaert博士的技术和科学专业知识高度补充。我们打算使用探路者资金来签约亨利，以制定最终用户参与的战略，以为我们提供业务模型开发的必要意见。通过以前的互动和经验，我们确定了一组潜在客户（有关更多详细信息，请参见“受益人”部分）。但是，他们的需求是多种多样的，并提出了不同的潜在业务模型，从销售传感器到提供与安装，操作和数据分析相关的服务。因此，我们旨在与潜在客户进行访谈，以了解其经营的业务环境，例如当前的需求，最困难的工作领域，已经进行了多少监控以及分配给水文数据的总预算的比例。这些信息将使我们能够确定一种或多种合适的业务模型，这是朝着制定业务计划的第一步。与最终用户互动和业务模型开发结合使用，我们还旨在探索知识产权环境，实施风险分析并确定相关竞争对手。