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Kando

Israel
Kokhav Ya'ir
2012
Private
< $10m
51 - 200
Open website

Kando was established in 2012 with the desire to lead a significant improvement in the quality of effluent discharged to the environment. Our game-changing solution is offered as a cloud-based SaaS. Using smart analysis of in-house developed algorithms, we radically reduce costs for water utilities. Kando provide's a complete 24/7, 360-degree overview of wastewater underground networks. Our solution represents a groundbreaking approach to wastewater networks, using our extensive field experience. We passionately provide unique and creative solutions, through a deep understanding of our client's needs, to create a cleaner environment for a better world.

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Kando’s end-to-end solution Clear Upstream provides continuous awareness of events in wastewater networks. IoT Sensing Units - Off-the-shelf water quality and dynamics sensors are integrated with a Controller and packaged into a robust, self-powered IoT unit. Introduced into the network at strategic locations via manholes, these units collect continuous data and transmit it to a cloud-based analytics engine. Some configurations of the IoT unit include automatic water samplers, primed to collect physical samples when triggered by real-time pollution events. Web-based Analytics Engine - Data collected by the sensors is pushed to Kando’s remote analytics platform, where thousands of datapoints are processed and cross-referenced to identify patterns and irregularities. This information is presented to clients as real-time pollution alerts and network health updates, using live maps, online dashboards, and text messages to ensure absolute clarity and maximum application value. Clear Upstream Methodology - Kando’s team examines each clients’ needs and network characteristics individually, using their analytics engine to generate a bespoke plan for IoT units’ optimal deployment. Units are then installed at strategic locations around the network, allowing for maximum data gathering at minimum cost. Unit locations are continuously reevaluated and optimized as more data is gathered and processed.

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Mei-Ashkelon Israel, Unity Water Australia, Mei-Carmel Israel, Ventura CA USA

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Kando is a provider of Industrial IoT analytics and modeling, and sensors technologies, and also active in the recycling and waste management industries.
Technologies
Analytics & Modeling
Big Data Analytics
Predictive Analytics
Sensors
Liquid Detection Sensors
Industries
Recycling & Waste Management
Kando’s Technology Stack maps Kando’s participation in the analytics and modeling, and sensors IoT technology stack.
  • Application Layer
  • Functional Applications
  • Cloud Layer
  • Platform as a Service
    Infrastructure as a Service
  • Edge Layer
  • Automation & Control
    Processors & Edge Intelligence
    Actuators
    Sensors
  • Devices Layer
  • Robots
    Drones
    Wearables
  • Supporting Technologies
  • Analytics & Modeling
    Application Infrastructure & Middleware
    Cybersecurity & Privacy
    Networks & Connectivity
Technological Capability
None
Minor
Moderate
Strong
Number of Podcasts1
EP 138 - What insight can water utility data provide to cities - Ricardo Gilead Baibich, CTO, Kando
Friday, Jul 22, 2022

In this episode, we interview Ricardo Baibich, CTO of Kando. We discuss the use of IoT data from water utilities to provide visibility into energy efficiency, infrastructure status, and population health risks and trends. We also explored the unique challenges faced by utilities due to the complexity of their networks and their inability to control the volume and quality of water flows into their systems.  

Kando is a data intelligence platform that brings data from waste water to help improve and support public health and the environment. Kando works with public authorities, municipalities, and water utilities to create operational visibility by leveraging IoT hardware and machine learning. 

 Key Questions: 

What are the biggest challenges that utilities face in managing waste water infrastructure? 

How can utilities use waste water data and machine learning to understand population health trends?  

How can legacy software and hardware be integrated into a modern connected system?  

How can data analytics make a circular water cycle possible and preserve water in arid regions? 

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