by The global public safety analytics market is primarily driven by the rising adoption of big data for ensuring public safety. Public safety analytics involves the use of complex algorithms and machine learning techniques to analyze huge amounts of data collected from various public safety systems such as surveillance cameras, emergency call systems, police databases, social media networks, and other internet-connected devices. This helps agencies identify patterns, predict future incidents, and deploy resources more efficiently to prevent accidents, crimes, and other threats. Public safety agencies use analytics solutions to gain actionable intelligence from video surveillance footage, 911 call records, crime statistics, and more. This helps law enforcement authorities identify habitual offenders, locate fugitives, detect fraudulent activities, and respond to emergencies in a timely manner.
The Global Public Safety Analytics Market Size is estimated to be valued at US$ 6.06 Bn in 2024 and is expected to exhibit a CAGR of 34% over the forecast period 2024 to 2031, as highlighted in a new report published by Coherent Market Insights.
Market key trends:
One of the major trends in the public safety analytics market is the integration of advanced technologies like artificial intelligence and machine learning. AI and ML algorithms are helping analyze huge amounts of public safety data much more efficiently. They can recognize patterns in video footage, detect anomalies, predict future crimes, and provide customized insights to officials. This is improving situational awareness for first responders. Another key trend is the growing adoption of predictive policing solutions that use analytics to forecast where and when crimes are most likely to occur based on historical data. This helps deploy police patrols proactively. Rising use of social media monitoring and geo-location data analytics by law enforcement agencies to track suspects and curb criminal activities is also a major trend in the market.
Porter’s Analysis
Threat of new entrants: The threat of new entrants in the public safety analytics market is moderate. Established players dominate the market and new entrants require significant investment in infrastructure and technology.
Bargaining power of buyers: The bargaining power of buyers is moderate. Buyers have a wide range of options to choose from due to the presence of numerous solution providers in the market.
Bargaining power of suppliers: The bargaining power of suppliers is low. The market has a large number of analytics solution providers and data vendors.
Threat of new substitutes: The threat of substitutes is low. There are limited product substitutes for public safety analytics solutions.
Competitive rivalry: Competition in the public safety analytics market is high due to the presence of numerous international and regional players. Players differentiate themselves based on solution offerings and pricing.
Key Takeaways
The global public safety analytics market is expected to witness high growth over the forecast period. The growing need for risk assessment and situational awareness and increasing use of predictive analytics by law enforcement agencies are fueling market growth.
Regional analysis: North America dominates the global public safety analytics market currently due to large scale implementation of advanced public safety programs. Asia Pacific is expected to grow at the fastest pace during the forecast period supported by increasing criminal activities and rising security concerns in emerging countries of the region.
Key players: Key players operating in the public safety analytics market are GoPuff, DoorDash, Instacart, Uber, Glovo, Rappi, Gorillas, Getir, Jokr, Zapp, Flink, 1520, Buyk, Deliveroo, Seazon, Yango Deli, Delivery Club, Bolt Food, Swiggy Instamart, and Blinkit. GoPuff and DoorDash are among the leading players investing in new solutions and partnerships for strengthening their position.
*Note:
1.Source: Coherent Market Insights, Public sources, Desk research
2.We have leveraged AI tools to mine information and compile it
