![]() Each element of our hardware (sensors, battery, IoT enabled controller, and autosampler) was specially designed or integrated to operate remotely within user networks.Kando’s solution includes dedicated software and hardware components, engineered to support precise, ‘event-triggered’ sample collection (in line with ISO 5667-10:2020): Generating a correlation curve against known wastewater characteristics, determined by comparative analysis of live condition reporting against laboratory sample analysis.īy tracing condition data over extended periods, Pulse can automatically generate long-term trend reports, supporting optimal capital investment, maintenance, and operative planning.Ĭan samples be taken only in response to a disturbance of these basic parameters to allow the sample to be collected precisely when the discharge event occurs?.Learning the average normal level of each measured parameter (EC, PH, ORP, temp).The wastewater quality baseline is generated by machine learning processes on two levels: The goal is to equip the system with a model of ‘normal’ network conditions, enabling it to identify changes that indicate possible pollution events. Kando’s web-based analytics engine determines baseline quality characteristics at each deployment location automatically. If you have more in-depth questions, feel free to connect with Anne-li Maron, Business DevelopmentįAQ discussing the capabilities and scope of Kando Pulse platform.Ĭan the system use machine learning to develop long-term condition trends and identify potential pollution events? On this page, you can find Frequent Questions & Answers (FAQ) regarding the Kando Pulse Platform.
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