One of the major concerns for smart cities, campuses & buildings is cybersecurity. With millions of edge endpoints and hundreds of systems in each city, the risks are enormous. SmartHub SPACES™ addresses these challenges with robust cybersecurity hygiene, infrastructure uptime monitoring, real-time alerts and actions, asset ledger tracking, remote management and diagnosis, advanced edge analytics, and ongoing AI/ML ops. It helps identify anomalies and potential security threats before they can cause harm, detect unauthorized access attempts or unusual data traffic patterns in real-time, and uses AI-driven models to predict and prevent cyber-attacks by learning from past incidents and adapting to new threat landscapes.

Our continuous learning ML models can significantly enhance the intelligence and efficiency of smart buildings & cities by enabling real-time adaptation to changing conditions & incidents. These models can continuously analyze data from various sensors, like air quality, temperature, humidity, occupancy, noise, parking, water quality, traffic, lighting & utilities usage sensors allowing the system to learn and optimize its operations over time. Detect anomalies in equipment performance & be on top of predicting maintenance needs before a failure occurs.

Meet the needs of modern workplaces and cities with hyperconnected edge infrastructure that can be managed to enhance quality of urban life. Leverage data that comes from this edge infrastructure to provide personalized experiences to citizens, city planners, employees & facility users. Irrespective of siloed systems and hardware (Edge endpoints), collect real-time data from various sources, such as traffic flows, energy usage, air quality, and public services. AI and ML algorithms analyze this data to optimize city operations, predict potential issues, and offer personalized services to residents. Additionally, citizens can interact with the city through a more sensory based infrastructure that is able to respond and provide recommendations.

Our GenAI adapter SDKs can help create adapters & integrations to all sorts of sensors and edge endpoints, in no time. Never again worry about connecting to and acquiring data from disparate devices. Focus on solving problems vs. worrying about managing edge infrastructure and trying to gain insights from your siloed edge operations. City/Smart Building planners can analyze data from sensors to optimize infrastructure, improve management, and enhance safety. Users benefit from real-time information on services like facilities availability, disruptions, safety risks, transportation, energy usage, and environmental conditions, enabling them to make informed decisions. Leadership teams gain insights into city, campus & building operations, allowing them to prioritize investments, improve resource allocation, and drive sustainable development initiatives.