“Retailers have been facing increased network problems related to capacity and reliability,” Grady said. Additionally, the services may also provide other desirable IT-based services such as VoIP, Wi-Fi, multicast and merchant connectivity. The Vector Security/Spacenet solution creates one point of accountability for retailers and provides proactive monitoring and support through VPNs, compliance services and secured hosting.
Retailers are also required to address increasing levels of customer data security, and may be limited by gaps in connectivity assets in specific geographic markets.” According to Michael Grady, executive vice president of Vector Security, “Bandwidth has become a major commodity in sustaining the increased level of data retailers commonly use to make key business decisions. Vector Security stated it will gain years of knowledge and experience from a proven provider, rather than develop these capabilities in-house over time. The arrangement allows Vector Security and Spacenet to focus on delivering their combined core competencies in an optimized way - today. If you have any questions, please reach out through the Topcoder Forum ( ).This arrangement will support various loss prevention, life safety and asset preservation applications from Vector Security, with a primary focus on broadband video monitoring. To further aid competitors, the SpaceNet 5 baseline is fully open source, and yields a score of 54. The first 20 competitors to reach a score of 50 (out of a possible 100) received a credit for 10 hours on a p3.2xlarge for training and improving their models. For the first time in SpaceNet history, the final submissions were tested on a mystery city dataset that was revealed and open sourced at the end of the Challenge. SpaceNet open sourced new data sets for the following cities: Moscow, Russia Mumbai, India and San Juan, Puerto Rico. You can find a detailed description of CosmiQ Works’ algorithmic baseline on their blog at The DownLinQ. The task of this challenge was to output a detailed graph structure with edges corresponding to roadways and nodes corresponding to intersections and end points, with estimates for route travel times on all detected edges. The SpaceNet 5 challenge sought to build upon the advances from SpaceNet 3 and test challenge participants to automatically extract road networks and routing information from satellite imagery, along with travel time estimates along all roadways, thereby permitting true optimal routing. Satellite or aerial imagery often provides the first large-scale data in such scenarios, rendering such imagery attractive. This statement is as true today as it was two years ago when the SpaceNet Partners announced the SpaceNet Challenge 3 focused on road network detection and routing. In a disaster response scenario, for example, pre-existing foundational maps are often rendered useless due to debris, flooding, or other obstructions.
Determining optimal routing paths in near real-time is at the heart of many humanitarian, civil, military, and commercial challenges.
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