DataCurrent Description
Real-time monitoring of rainfall through rain gauges enables operations personnel to be alerted about potential flooding or sewer overflow situations. By closely tracking and evaluating precipitation levels at various sites, it becomes possible to estimate rainfall in areas that are not directly monitored, a method known as the “Distributed Rainfall Modelling Technique” (DRMT). The integration of rainfall radar data with readings from rain gauges facilitates the creation of enhanced rainfall coverage maps. Furthermore, examining historical rainfall data helps in constructing rainfall intensity-duration curves, which can be compared to the design intensity-duration-frequency curves of the region, aiding in the identification of return periods for recorded events through forensic analysis. In addition, new intensity-duration-frequency curves can be generated to inform the design of drainage infrastructure, including sewers, channels, and storage facilities. Continuous flow monitoring, coupled with data analysis, contributes to the development of rainfall versus stormwater runoff response curves, which are essential for calibrating drainage system models effectively. This comprehensive approach ensures that urban planning and flood management strategies are well-informed and responsive to actual conditions.
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Denodo is a logical data management platform built to help enterprises unify, govern, and deliver trusted data across complex technology environments. It connects data from cloud, on-premises, SaaS, third-party, and multi-cloud systems without copying or duplicating the information. The platform gives organizations a single trusted view of distributed data, helping analytics teams, business users, and AI agents access current information more efficiently. Denodo supports trustworthy agentic AI by combining live data access with business semantics, centralized governance, compliance controls, and lineage. Its self-service data marketplace allows users to find, prepare, and use governed data while reducing dependence on IT teams. The platform also supports natural language search, personalized data delivery, and role-specific views so users can get data with the right business meaning. Denodo helps organizations improve data lakehouse investments by giving teams optimized access to data beyond a single repository. Its real-time delivery capabilities help operations, analytics, and AI systems make decisions based on current information instead of stale copies. By reducing integration time and improving time-to-insight, Denodo gives enterprises a trusted data foundation for AI, analytics, and digital transformation.
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Redlist is a reliability centered maintenance platform built for industrial teams that need more from their CMMS. Where traditional maintenance software stops at the work order, Redlist continues to the shop floor, tracking every lubrication point, inspection task, and operator action.
The platform runs on web, iOS, and Android with full offline functionality, purpose-built for technicians in plants, mines, and refineries where connectivity is unreliable.
Lubrication Management
Redlist manages lubrication at the individual point level, assigning the correct lubricant, volume, and frequency to every grease fitting, oil drain, and sample port. Routes are executed digitally, replacing paper-based systems and eliminating the pencil-whipping that hides missed tasks. Oil analysis results from labs integrate directly so technicians see condition data alongside their route.
CMMS and Asset Management
Manage assets from the enterprise level down to individual components. Create work orders, build PM templates, track parts inventory, and schedule predictive maintenance. Connects to existing ERP and CMMS systems including SAP, Oracle EAM, JDE, and Maximo, bridging the gap between enterprise software and field execution.
Operator Basic Care
Enable frontline operators to perform guided daily inspections and basic maintenance tasks, building a digital record of institutional knowledge that would otherwise be lost when experienced technicians retire.
AI Agents
Nine purpose-built agents for FMEA analysis, RCM-based PM development, oil analysis interpretation, vibration diagnostics, and lubrication optimization.
Serving mining, oil and gas, chemical processing, food and beverage, packaging, paper and corrugated, and manufacturing. Deployed under 100 days.
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OpenFlows CivilStorm
OpenFlows CivilStorm is an advanced software tool designed for the thorough modeling and analysis of stormwater systems. Modeling these systems can be intricate due to various factors such as flow backups, pipe surcharges, and other complexities. This software addresses all facets of stormwater management, allowing users to identify bottlenecks in the system, enhance capacity, and mitigate flooding occurrences to ensure compliance with regulatory standards. By utilizing optimized network designs and comprehensive master plans, users can reduce their capital expenditures on infrastructure improvements. OpenFlows CivilStorm effectively analyzes a wide range of stormwater system components, including rainfall, runoff, inlet capture, bypass mechanisms, as well as gravity and pressure piping structures. Users can also model ponds, outlet structures, open channels, and culverts, providing a full spectrum of stormwater modeling capabilities. Furthermore, it allows for the assessment of both pressure and free-surface flow conditions across complex networks, enabling the design of sophisticated pond outlets under varying tailwater scenarios. It also supports the integration of weirs, orifices, culverts, risers, and inlet boxes into system designs, making it a versatile choice for stormwater management professionals. Thus, OpenFlows CivilStorm stands as an essential tool for those seeking to optimize their stormwater systems efficiently.
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AWS IoT Analytics
The data generated by IoT devices is predominantly unstructured, posing challenges for analysis using conventional analytics and business intelligence tools that cater to structured data formats. This type of data is often derived from devices that capture inherently noisy processes like temperature, motion, or sound, leading to frequent occurrences of significant gaps, corrupted messages, and erroneous readings that necessitate cleansing prior to any analytical work. Moreover, the significance of IoT data frequently relies on supplementary inputs from third-party data sources. For instance, vineyard irrigation systems enhance moisture sensor readings with rainfall data, assisting farmers in making informed decisions on when to irrigate their crops, thereby optimizing water usage and boosting harvest yields. AWS IoT Analytics simplifies and automates the complex steps involved in analyzing data from IoT devices, making it easier for users to gain insights. This service is fully managed and operates on a pay-as-you-go model, ensuring automatic scaling to accommodate varying data volumes. Consequently, organizations can leverage AWS IoT Analytics to advance their operational efficiencies and make data-driven decisions with greater ease.
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Company Details
Company:
Smart City Water
Headquarters:
Canada
Website:
smartcitywater.ca/datacurrent/
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