On the 23rd of December, Webank and Terminus announced officially that they have established the “AIoT Joint Laboratory”. The two parties will jointly research the field of “Artificial Intelligence + Internet of Things” (AI + IoT), combined with WeBank’s AI technology represented by federated learning and the rich business experience of Terminus ‘s urban management. The cooperation will help upgrade the smart city and intelligence security, such as urban management, public security and community. The deputy manager of the WeBank AI group, Tianjian Chen and Yi Zhang, the general manager of the ecosystem product center of Terminus technology group, inaugurated the joint laboratory and signed the cooperation agreement.


From IoT to AIoT, AI becomes the key to the transition

In the recent year, with the rapid development of IoT technology, “smart city”, “intelligent security” and “intelligent transportation” has begun to come into reality. However, during the process of the transition from IoT to AIoT, the development of technology is quite bumpy and facing many challenges:

One is the information silo. Taking the implementation of smart cities as an example, the different department manages its information. It is difficult for them to share information and thus it became the information silo, which increased the difficulties of management and decision-making.

Second is the “non-standard” situation. With the city development, the magnitude of data keeps expanding. Because of the lack of uniform interface standards and the difficulty to collaborate and integrate the specification, the value of data is hard to play effectively.

The third is the need for “data security” on how to search, storage and use the data based on “safety compliance”, avoiding to abuse data. This is the common request of self-privacy protection from the current legal regulation and public. It is also a key technology in the development of the industry.

Under this background, WeBank cooperated with Terminus to establish “AIoT Joint Laboratory”. It will open a new development of AIoT through the federated learning technology to overcome the difficulty of IoT data. As the new generation AI technology, federated learning can jointly build models to improve the performance of AI models under the premise of participant’s data never leaving the local storage. It is reported that the frontier of AI technology, federated learning is pioneered by WeBank in China. Currently, it has been applied to smart loans, smart risk management, anomaly detection and, other business scenarios to help promote the smart city, intelligent finance and other industries. However, as a leader of smart city-class IoT platforms in China, Terminus has served lots of scenarios in the AIoT applications, such as public security, population, fire control, police service and travel, owning a deep industry experience. With the powerful AI ability, WeBank combined the rich business experience of Terminus. They will greatly accelerate the transition from IoT to AIoT, thereby bringing a broader application market for the IoT industry.

WeBank and Terminus focus on AIoT, the result of “smart community” is outstanding

The “AIoT Joint Laboratory” choose the “Smart community” as the starting point to accelerate AIoT research and practical application. The federated trace prediction model researched by the cooperation between WeBank and Terminus has been implemented officially in some areas of Beijing. It is known that, based on the community security data, federated model connects many communities and combines the timing and space of the trip, and historical trip experience under the premise of data keeping in the private storage of the community server. It will use the federated learning technology for modeling with the real-time data monitoring and AI visual analysis method, to intelligently forecast the timing and location that the authorized person who needs help may appear in it. Therefore, it can analyze intelligently different peoples. While providing targeted services for community residents, it also provides technical support for delicacy management of community and urban population.

For example, the federated trace forecasting model can conduct the feature extraction of the track for solitary elderly and build model and judges the behavior of the elderly based on the model. If there is an abnormal deviation at the monitoring time, it is judged as a trajectory anomaly. In this way, different warning rules can be set for the elderly who have not been out for a long time and corresponding warnings can be given to inform the relatives of the elderly and the community management staff, so they can provide help as soon as possible.

The trace forecasting model of the elderly

Besides, the community neighborhood committee and management office can know the life of old mem according to the access records. Combined with the early warning system, the staff can visit the specific person. It not only keeps residents safe but also it reflects the care of people’s livelihood in the community, helping the construction of security and community.

In addition to providing security warnings and targeted care for vulnerable groups such as the elderly and children, this model is also suitable for community security, such as through precautionary control of illegal drug users to change the traditional person-to-case investigation mode to avoid threats and irreversible negative impacts on the lives and property of the people.

The implementation of the federated trace forecasting model not only can provide a more safety and comfortable living environment for the community residences, but it also reduces the management cost of property management and raise the management level of the intelligence, digitization and convenience, accelerating the coming of “smart community”.


Keep accelerating the implementation of AIoT

The federated trace forecasting model is implemented in the “smart community”, which is the good beginning of “AIoT Joint Laboratory”. It is also another milestone in the development of AIoT, but it is far from the end. In the future, based on the cooperation to develop the smart community prediction model, the two parties will keep focusing on the AIoT and improve the federated learning technology, unleash the potential of multidimensional data. In the cooperation of AI technology and big data, more industrial applications and solutions will be generated to support richer scenario requirements and help upgrade more intelligence industry. As the deputy manager of the WeBank AI department, Tianjian Chen said, “Technology must land in the business scene. AI can genuinely liberate the human workforce, thereby enabling the technology inclusive industry, the general public, and the inclusive society.” Only in this way, lots of the “smart community” can connect one point after another, gradually form a line. Then form a network of a smart city for us to have intelligent life.


About WeBank AI group:

WeBank AI group is a top artificial intelligence research team under Shenzhen Qianhai WeBank Co., Ltd. The AI team is committed to exploring new ways of Fintech with autonomous, controllable, secure and reliable AI technology, and leading the new direction of the AI industry. Based on the industry application scenarios and starting from the finance, the AI team has many explorations on the frontier of AI. The representative of achievements included federated learning, transfer learning and so on. As a leader in federated learning, WeBank not only proposes the general solution “federated transfer learning” for the first time in all over the world, but it also leads and promotes the AI collaboration ecosystem construction under the protection of data privacy.


About Terminus:

Terminus is a new technology company under China Everbright Group’s development strategy and also an intelligent IoT unicorn company supported by China Everbright Group. Terminus takes the lead in proposing the AIoT technology structure and uses it. Providing the intelligent technology service of public management and public service for government and enterprises, it aims to become the smart scenario service company leading in the world and create industry-leading solutions in the scenarios of community, public utilities, electricity and energy, and public service. Terminus also set up research centers in Beijing, Shanghai, Chongqing, Wuhan, Shenzhen and other cities. Terminus has owned 720 domestic patents including 417 patents for innovation and it is selected into the authoritative IT research and consulting company Gartner report for six times and has been unanimously recognized by the industry.

More information about federated learning, please come to our FedAI official website: https://www.fedai.org/