security solutions

In today's era where digital transformation and information upgrading are everywhere, the implementation of Smart twins, that is, the implementation of smart building digital twins, is indeed a hot topic that many friends who are engaged in the construction industry, property operation and maintenance, and smart city planning, are most concerned about; after all, who doesn't want to make the buildings they are responsible for smarter, better managed, and more money-saving through such a high-tech thing? The so-called smart building digital twin, in short, is not that simple. It is to use computer software to copy the building that already exists in reality or is still in the design stage in the virtual computer world, with a 1:1 ratio of the same "digital stand-in"! This substitute not only looks like it, but can also collect various data in the real building in real time through various sensors, Internet of Things devices, etc., such as temperature, humidity, lighting, and equipment operation status, and then simultaneously reflect it in the virtual model, allowing the manager to clearly understand the overall picture of the entire building anytime and anywhere, and even simulate different working conditions and predict possible problems in the future. Its functions are so powerful! (Provide global procurement services for weak current intelligent products!)

It is not a simple thing to do by just shouting about concepts and making a beautiful demonstration demo. There are too many pitfalls and too many links to pay attention to. You have to dig into details step by step, one module at a time, and then advance step by step.

1. The requirements sorting and goal setting module are the starting point and must not be skipped! This matter has to start from the most fundamental question, which is why we are going to be a digital twin: do we want to simply improve the energy efficiency of the building and reduce electricity and property fees? Or do you want to improve the safety management level of the building and avoid risks such as fires and security loopholes? Or is it to provide a more comfortable and personalized experience to those working in the building and visitors? For different goals, the technical routes selected later, the types of data collected, and the accuracy requirements of the simulation model will be a thousand miles apart! For example, if the focus is on energy conservation, the data collection of HVAC and lighting systems must be particularly fine; if the focus is on security, the real-time data access of video surveillance, fire alarm, and access control systems must be placed in the most priority.

2. Data collection, IoT network construction is the core support, and without data, everything is empty talk! This is like installing a nervous system for a person – there are many types of sensors in every corner of the building, where we can think of, such as temperature and humidity sensors, light intensity sensors, electricity meter and water meter sensors, sensors for detection equipment (oh, vibration), detectors for personnel occupation, etc. Then, it also needs to be equipped with a reliable data transmission network. Maybe Wi-Fi 6 is not enough. Sometimes it may also be necessary to use low-power wide-area network technologies such as LoRa and NB-IoT designed specifically for IoT devices. Even 5G may come in handy to ensure that these massive sensor data can be transmitted to the subsequent platforms in a stable, real-time, or in the period we set. This network-based project is quite huge. We have to consider signal coverage, data transmission delay, and equipment power supply issues. We can't replace the battery every now and then

3. Three-dimensional modeling and virtual engine selection are the "shapes" of digital twins! This step is to get the "shape" of the building into the computer. You can import it with CAD drawings, or simply send a special team (field measurement team) to carry a laser scanner to scan it on site. In short, you have to create a three-dimensional model that is exactly the same as the appearance and internal structure of the real building. Even the steps there are and how many sockets there are on the wall, it is best to model clearly. The more refined the better. Of course, it depends on the application requirements. Model (too detailed model) can sometimes slow down the system operation speed. It is wise to find a balance between accuracy and performance. Then, which platform should this model be put on? Should we use some more general game engines to modify it, or use the industry's special digital twin platform suite? This also needs to be carefully weighed based on the project budget and the skills mastered by the technical team.

When promoting these modules, you will definitely encounter all kinds of messy questions and confusions. Let me talk about some of the most asked questions you have asked, and give you some references.

Then the question is, is this digital twin system very expensive to build and use in the future? Is it necessary to do something so complicated for smaller building projects, such as a newly built small office building or a shopping mall? The money issue is indeed an unavoidable topic! Initial investment, software and hardware procurement, sensor installation, and model construction are indeed not a small amount. But with Smart building digital twin implementation, we have to calculate the long-term accounts, for example, through optimization management, how much energy costs can be saved in a year? By predicting equipment failures in advance, the losses caused by sudden downtime are also a lot of money! As for small buildings, it is not impossible to do it at all. You can start with the most core and most profitable systems, such as smart lighting and smart air conditioning, and build a simplified version of digital twins, such as only building one floor, or focusing on controlling a few key areas, and then checking for the effect, and then slowly expanding, and running quickly in small steps is not bad.

There is so much data, and it is collected every day, and there is structural data of the building itself, real-time data of equipment operation, and data of personnel activities. So much data is piled together, will it become a "garbage dump" of information? It is dazzling to see it, but it cannot find useful information. It may even be because of too much data, the system is stuck and cannot be used? Your concern is too right, it is a typical "data glut" problem! Therefore, from the beginning, the concept of data governance should be introduced and basic work such as data classification, data cleaning, and data standardization should be done. Not all data is thrown into the system. We must selectively collect data that is strongly related to the goals we set initially; and also set data weights, focus on display and prioritize analysis of important data; build data index (that is, index) to improve query efficiency. Now many digital twin platforms also come with big data analysis functions, which can automatically help us filter out key information and abnormal data, so as to avoid becoming a good-looking but useless "data chimney".

The building has been built long ago. The older (old building) does not reserve so many sensor installation locations and wiring spaces. Moreover, many of the existing old elevators and air conditioning equipment cannot be directly connected to the Internet and the data cannot be derived. Can digital twins be created in this situation? Do you have to watch the new building be able to use new technology, and the old building has nothing to do with it? This situation is too common in reality, and a lot of old buildings are facing this problem! But it doesn’t mean that there is no way to do it, there are still (workarounds). For example, when installing sensors, you can try to choose a wiring-free, battery-powered wireless sensor, which is convenient and fast to install. For some difficult places where holes are not easy to drill, you can even use a temporary but effective way to fix it with magnet sucking and super glue, as long as data can be obtained. In terms of device data, you can install some external contact sensors to indirectly read data. There is now something called (modified gateway), which can convert device data using RS485 and these old protocols into Ethernet or Wi-Fi data that can be accessed to the Internet. If the budget allows, you can also consider gradually replacing some key, too old core devices into new products with smart interfaces.

Overall, nothing is simple, especially for complex projects like smart building digital twins that sound very high-end, involve interdisciplinary and multi-technology integration. From the initial demand survey, to the intermediate technology selection, hardware laying, software development, and later system online debugging, personnel training, and continuous operation and maintenance optimization – every link requires a lot of time, energy and money to polish. Moreover, this thing is not a one-time transaction. Once the digital twin model is built and the data is connected, everything is not going to be good or done once and for all. It has to be updated continuously according to changes in the real building, such as decoration and modification, equipment replacement, and the data collection strategy must also be adjusted according to changes in business needs. Just like a car, it must be maintained regularly and added fuel from time to time to run smoothly and easily. Therefore, if you want to truly make, use, see real benefits, be patient, careful and continuous investment, and have a professional team that understands business and technology, that is absolutely indispensable core elements!