Maintaining Situational Awareness
Public safety entities are challenged by various threats and alerts daily. Loaded with rich and informative data, social media content can help expedite interventions, while leveraging impact and efficacy of mediations when made accessible to government organizations. From photographs of emergencies, to posts about crime in progress, users inundate social media platforms with invaluable content about current events pertinent to public safety. Given the sheer amount of location-based online data, collecting, processing, prioritizing, and taking appropriate actions present serious challenges. The demand for sophisticated solutions generating real-time intelligence is now critical to the progress of public safety entities worldwide.
Cobwebs’ advanced web intelligence tool aids public safety entities in attaining unmatched situational awareness. Our revolutionary search engine scans the worldwide web, analyzing its vast data for deep intelligence insights. Querying data from multiple sources, our tools generate critical geo-located alerts in real time. Cobwebs’ technology monitors and analyzes current and historical location-based data with advanced artificial intelligence algorithms, providing comprehensive, relevant search results and alerts. Leverage and enforce public safety in acquiring everything from photos, to videos, to text content, and take organizational problem solving processes to the next level with every click.
GEOFENCING AND ALERTING
Cobwebs provides geolocation discovery modules, empowering users with simplified extraction of web content from geographically defined location-based radiuses, via GPS-derived posts, photos, videos, statuses and more. Our system’s AI tools geolocate text entities while offering enhanced geofencing capabilities, analytics and alerts.
Monitor social media, surface, deep and dark web layers continuously to collect new data and receive relevant intelligence, insight, and alerts. Leading artificial intelligence algorithms conduct statistical calculations with learned models, offering predictive insights, like deviations in targets’ activities, changes in sentiment and other unconventional anomalies.