Unifying Crowdkeep’s IoT Platform with Veea’s Edge Platform creates a wholistic platform managed at the edge, optimizing operational efficiencies, maximizing safety, and streamlining campus and construction site management
Crowdkeep, the leading Internet of Things (IoT) platform in asset, people, and condition tracking; and Veea (NASDAQ: VEEA), a first-to-market pioneer in hyperconverged multiaccess networks with AI-driven cybersecurity, have announced their partnership to integrate their respective technologies into a singular, tailored solution to track assets, people, and conditions across a variety of use cases complementing a plethora of edge applications, developed by Veea and its ecosystem partners, that together run on Veea Edge Platform.
The combined capabilities of Crowdkeep and Veea is offered through an AI-enabled multiaccess edge computing platform with 4G or 5G connectivity, an IoT gateway and a comprehensive cloud backend for device and application management, and the associated data analytics, enabling organizations to maintain visibility on employees, students or guests at a venue, manage and track valuable assets along with visual displays of camera streams, event notifications, utilization rates and footfall analytics with heatmaps. The solution also offers management, monitoring, programming or automation of a) IoT endpoints (e.g., cameras, smart locks, gunshot audio detector, or leak detectors), b) access authorization and lockdown management, c) energy consumption (e.g., lighting, HVAC or refrigeration), d) environmental conditions like air or water quality, e) occupancy (i.e., with cameras or occupancy sensors), f) compliance, safety (e.g., accident or fight detection with cameras), g) digital health with alerts (i.e., sensors and cameras), h) predictive maintenance, i) management of cached content or digital forms at the edge for privacy, secure delivery when in proximity, or when latency sensitive, j) smart check-outs, and k) interactive digital displays with language translations, among numerous other features.
With optimized solutions for construction, education, healthcare, and logistics, the combined Crowdkeep – Veea platform features capabilities and applications such as automated attendance tracking, seamless timesheet approvals, industry-specific functionalities such as emergency response systems for schools or geo-fenced hazardous areas for construction sites with notification capabilities that support event triggers for automated functions, alarms and the full range of private or public communications at the edge.
Automated attendance tracking allows administrators to track employee/student attendance and streamlines staff timesheet completion, while smart asset management offers the ability to track the location of all valuable assets, such as laptops, valuable tools or machinery with AI-powered usage analytics and a recommendation engine for optimal resource allocation by the school administrators and staff. Integrations for environmental monitoring allow administrators to monitor, detect, control and/or automate conditions like fire or smoking/vaping with notifications, temperature, air and water quality. Veea’s implementation of Containerized Portable Niagara Framework from Tridium allows additional energy and building management use cases.
The emergency response solutions not only ensures compliance to newly-passed legislation like Alyssa’s Law, but goes farther, allowing parents direct monitoring access to their children with a simple wristband or a tag at all times while on campus. The platform’s people tracking technology is supported by a mesh IoT network, which triangulates a user’s location through the wearable tag with real-time accuracy, guaranteeing the most reliable information for authorities in emergency situations.
The combined platform, with distributed computing nodes over a multiaccess mesh connectivity network, is capable of collecting enormous amounts of data from connected devices (e.g., user devices, cameras and sensors) where a machine learning application can be employed to make data-driven predictions or decisions with fusion of logic derived from data collected from different sensors and cameras. The Edge AI is delivered through a computer vision application with the ability to interpret and analyze camera streams and time-lapse images to then turn them into actionable insights, detecting both anomalies and progress as well as workers’ location on the job site and behavior. More complex features such as neural reasoning with digital twins can extract complex events and trigger alerts from captured data, for example, to reconstruct complex building structures and detect deviations. The combined offerings span across a range of other industries and verticals.
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