Are you getting the spatial insights required from your IoT networks?
Companies & cities are investing millions in connected sensors, but achieving an ROI is dependent on setting up robust IoT analytics that process the location data generated into tangible insights.
1. Bring your data
Import your own location data & enrich it with our data streams.
Analyze historic sensor-generated location data to inform future planning & resource allocation.
Provide real-time, interactive dashboards to decision makers in cities & government to help them reduce costs & build more efficient cities.
IoT Analytics Use Cases
Waste Collection: Reduce waste management costs using fill level sensors in trash cans across cities, allowing more efficient pick up routes & frequency.
Energy Management: Reduce street lightning costs using spatial analytics to understand demand by time & location.
Traffic Management: Optimize public transport infrastructure, such as bikes, buses, trains, & metro services to reduce traffic & improve road safety.
Climate Insights: Climate Insights: Predict climate-related risks affecting the built environment, and drive more informed infrastructure decisions across government departments.
Air Quality Monitoring: Monitor the emission of CO2 with pollution & temperature sensors to improve environmental management strategies & clean air planning.
Electric Vehicle Charging: Identify prime locations for electric vehicle charging points based on demand, proximity & accessibility to key segments with a higher propensity to use or buy electric vehicles.
Smart Health: Make critical decisions on resource allocation for public health services across your city, using Open Data alongside human mobility data.
Citizen Safety: Identify higher risk locations across your city, predicting & analyzing crime data to ensure preventative measures are taken to improve citizen safety.
Watch this webinar to review a practical approach to using LLMs in geospatial analytics using a progressive approach to start small and grow.
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Explore with us how IoT Analytics use cases are driven by geospatial data for catastrophe modeling, in smart cities and supply chains.
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