In today’s hyper-connected world, where emerging threats lurk around every corner, securing Edge and IoT devices
Power your smart agriculture initiatives (whether you are an agricultural university, research organization or a commercial grower) with SmartHub GROW™. Leverage our advanced edge technologies, AI, and machine learning capabilities to optimize farming practices for better monitoring, management and yields.
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AI/ML driven food production & sustainability solutions
Precise monitoring and control of environmental conditions, crop health, and soil quality through IoT sensors ensures that plants receive the right amount of water, nutrients, and sunlight. Agricultural researchers can measure, monitor and perform analytics around specific factors or combination of factors impacting crop growth under varying levels of irrigation & fertilization. This can result in higher crop yields, reduced resource wastage, and more sustainable farming practices.
Manage pest outbreaks, automate irrigation and harvesting, and provide real-time data analytics to farmers. This helps them make informed decisions that improve efficiency, reduce costs, and minimize environmental impact. Our ML models help predict variance in conditions that might result in potential diseases, across your crops, orchards and agricultural fields.
We integrate with some of the top OEMs which are gold-standard sensors and devices used in agricultural industry. Our integrations spans LoRaWAN gateways, weather monitoring stations, infrared, radiometry, PAR, SAP Meters, Canopy sensors, SAP flow meters, Leaf spectrometers, cross stress index meters, precision temperature, humidity, barometric pressure, saturated vapor pressure, vapor pressure, vapor pressure deficit, dew point and vapor density sensors & solar panels.
The Treatment & Replicates capability in SmartHub Grow™ enables precise measurement, monitoring, and analytics by leveraging various IoT sensors deployed in agricultural settings. It allows users to assess the impact of specific factors or combinations of factors on crop growth, particularly when exposed to different levels of irrigation and fertilization. Advanced KPIs such as mean, median, and mode can be measured across treatments, with the ability to tag treatments and outcomes for better analysis. This feature is designed to scale, supporting research faculty, professors, and students in their studies and projects.
SmartHub Grow™ collects real-time data on soil moisture, temperature, humidity, and other environmental factors across agricultural fields, orchards, and greenhouses. By integrating spatial data such as GPS and satellite imagery, the software generates spatial overlays that visualize sensor deployment locations, uptime/downtime, alerts, notifications, and variations in soil conditions, crop health, and pest infestations. This granular insight, paired with trend analysis, machine learning models, and pattern recognition, empowers farmers, faculty, and students to adopt precision farming techniques. They can optimize water usage, fertilizer application, and pest control, enhancing both productivity and sustainability.
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