FinancialBuzz.com’s latest Buzz on the Street Show: Featuring Our Corporate News Recap on “First Responder Appoints Star Finance GmbH to Assist with European Market Development Efforts.”
First Responder Technologies Inc. (CSE: WPN) a developer of WiFi-based technologies to detect and deter mass shooting and terror attacks involving concealed weapons, is pleased to announce it has entered into an Investor Relations Agreement with Star Finance GmbH, a Swiss-based company, for European corporate communication services. Star Finance has offices in Steinhausen, Switzerland, and Cologne, Germany.
First Responder Technologies Inc. (the “Company“) is a technology development company that commercializes academic and internally developed intellectual property for use in the public safety market. The Company is developing a WiFi-based technology, based in part, on academic research licensed from Rutgers , the State University of New Jersey (“ Rutgers “) that can be used to detect concealed weapons. The Company’s threat detection technology line of business was created to capture a significant portion of the global weapons detection systems market, and in particular, the global perimeter security detection market. In the Company’s view, WiFi‐based threat detection technology may be utilized by a wide range of facilities, including schools, places of worship, shopping centres and theatres, to not only make their premises secure, but also reduce their cost of security, from the interior of a facility to the perimeter.
Over the course of the last decade, the rising number of mass shootings at public places has renewed the focus on innovative threat-detection technologies. Various commercial enterprises such as malls, cafes and theaters are exploring using advanced technological systems to prevent unfortunate events and accidents. For example, earlier in 2018, the retail giant Walmart announced that it had tested facial recognition technology for its security systems. However, the cost for these new state-of-the-art technologies is also rising and governments have now had to increase their spending in order to lock in contracts and supply their specific military branches. Countries such as China, Israel, Russia, and the U.S. allocate a significant portion of their budgets into defense. For example, in 2019 the U.S. “Department of Homeland Security” estimated a security budget worth USD 51.7 Billion for the fiscal year 2020, compared to the USD 47.5 Billion budget for the fiscal year 2019. Business and governments are also investing in Artificial Intelligence (AI) and the Internet of Things (IoT) technologies to further enhance these systems, which in turn, is anticipated to help support the threat-detection systems market in the near future. Additionally, according Zion Market Research, the global threat-detection systems market accounted for USD 70.2 Billion in 2018 and is expected to reach USD 163.4 Billion by 2025. It is also expected to expand at a CAGR of around 12.8% between 2019 and 2025.
Currently, the threat-detection market is very segmented. By type, the global threat-detection systems market is fragmented into explosive detection, radiological and nuclear detection, narcotics detection, chemical and biological detection, intrusion detection, and others. Overall, the video-surveillance systems segment is expected to grow considerably in the future, in large part thanks to the increasing demand for surveillance cameras in developing economies of the Asia-Pacific region. Meanwhile, the gunshot-detection system market is also projected to grow from USD 726.3 Million in 2016 to USD 3,099.8 Million in 2022 while at a CAGR of 27.36%, according to a report by MarketsandMarkets. The report also indicates that, based on installation type, the gunshot-detection systems market is dominated by the fixed segment, and this segment is projected to grow at the highest CAGR during the forecast period. Fixed gunshot-detection systems use the acoustic sensor node detection technology to ascertain a gunshot event and installations are carried out at a specific height from the ground.
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