At present, most scenarios have covered traditional security equipment, but the system is outdated and the effect is poor. Upgrading projects have become the main battlefield of the fragmented market. Of course, there are also direct application needs in the new market. Therefore, the software and hardware upgrading of the traditional security system will become the future demand growth point of the pan-security industry, and front-end equipment such as video surveillance, portrait recognition, and access control will usher in a large-scale development space.
The update and iteration of new technologies will inevitably lead to continuous exchange of blood in related industries. At present, under the impact of new technologies such as 5G, artificial intelligence, and cloud computing, the security industry has become more and more rich in product functions and blurred boundaries. more extensive.
The security industry has both government-led centralized urban security projects, as well as fragmented small projects caused by non-standard demands scattered in various regions and industries. Enterprises that are good at operating the entire project in the centralized market are difficult to operate in the fragmented market. Focused on exertion, so the fragmented form has existed for a long time. The conclusion is that we have entered a new era – the era of pan-security.
In the era of pan-security, many unmet personalized needs are expected to be realized, and the phenomenon of “fragmentation” in the security industry will become more and more obvious. According to research by authoritative institutions in the industry, from the perspective of project volume and customer groups, the security market is distributed in a concentrated (short-end market) and fragmented (long-tail market).
The fragmented market with long tail effect emphasizes “individuation” and “customer needs”. If these small markets are superimposed, it can be seen that the demand potential is very large.
As the Xueliang Project and the Safe City are gradually coming to an end, many data show that the pan-security industry will sink into the capillaries of the city and integrate into all aspects of life scenarios, and the personalized needs for different scenarios will gradually become prominent and fragmented. The market is expected to become a new growth driver for the security industry.
Standardization is a sign of a giant monopoly. In the current pan-security fragmented market, the standardization of a single scenario has improved, but customer needs are generally not limited to a single application scenario.
Based on the in-depth understanding of the needs of different scenarios, security manufacturers develop corresponding highly integrated hardware and matching data processing, AI intelligence, and business process-based management and control platforms, and provide customers with one-stop solutions in a standardized way in subdivided fields. Program.
Security needs can be divided into two categories: market needs and policy needs. The policy demand means that the end user builds a security system according to the national and local policy requirements, which is a rigid demand; while the market demand is to build a security system according to the end user’s own security needs, which mostly depends on the end user’s security awareness or the purpose to be achieved.
At present, most scenarios have covered traditional security equipment, but the system is outdated and the effect is poor. Upgrading projects have become the main battlefield of the fragmented market. Of course, there are also direct application needs in the new market. Therefore, the software and hardware upgrading of the traditional security system will become the future demand growth point of the pan-security industry, and front-end equipment such as video surveillance, portrait recognition, and access control will usher in a large-scale development space.
According to statistics, the proportion of smart cameras on the market is less than 3%. According to Omdia, shipments of AI cameras (deploying deep learning algorithms) will account for 10% of network camera shipments in 2019 and 63% in 2024.