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AI for Good Innovate for Impact



                   Use Case - 5: Explosion-Proof Intelligent Inspection Robot Solution                              4.5: Manufacturing














               Organization: Sevnce Robotics Co., Ltd.

               Contact person: - Chengcheng Wang; wangchengcheng@ sevnce .com

               Country: China


               1      Use Case Summary Table

                Item                    Details

                Category                Manufacturing
                Problem Addressed       In scenarios such as traditional manual inspection of power facili-
                                        ties and industrial equipment, there are issues like low efficiency,
                                        high safety risks, and incomplete data collection. Existing inspec-
                                        tion robots have insufficient intelligence and struggle to adapt to
                                        complex environments and handle abnormal situations autono-
                                        mously.

                Key Aspects of Solution  Adopt embodied intelligence technology and combine multimodal
                                        sensors (such as infrared thermal imagers, high - definition cameras,
                                        gas detectors, etc.) to achieve environmental and equipment status
                                        perception. Utilize deep learning and reinforcement learning algo-
                                        rithms to endow robots with autonomous path planning, abnormal
                                        identification, and emergency response capabilities. Through edge
                                        computing and cloud - based data analysis, realize real - time moni-
                                        toring of equipment status and predictive maintenance.

                Technology Keywords     Embodied intelligence, multimodal sensors, deep learning, rein-
                                        forcement learning, edge computing, predictive maintenance

                Data Availability       Private. Data is sourced from sensor data collection in actual inspec-
                                        tion scenarios, historical equipment operation data, etc.

                Metadata (Type of Data)  Visual data (equipment appearance images), thermal imaging data
                                        (equipment temperature distribution), gas concentration data, vibra-
                                        tion data, sound data
                Model  Training  and  Based on a large number of equipment images and operation data,
                Fine-Tuning             use deep learning models to train for abnormal feature identifica-
                                        tion. Optimize the robot's inspection path planning and decision
                                        - making model in complex environments through reinforcement
                                        learning.

                Testbeds or Pilot Deploy- Pilot projects were carried out in a large - scale substation and a
                ments                   chemical plant. Link:








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