28 results about "Inventory analysis" patented technology

A system and method for streamlining and accelerating cloud migration processes may include a plurality of modules including an adaptive prompt module configured to create a library of prompts, maintain the library of prompts, and select one or more prompts from at least one large language model (LLM) based on a prompt strategy that may consider which prompts in the library are most likely to elicit accurate and relevant responses from the at least one LLM. Another module may perform inventory analysis to enhance the prompt strategy. A third module may perform workload transformations based on the library of prompts, and a fourth module may provide validation mechanisms. The adaptive prompt module also may include a self-learning module configured to enable integration across the plurality of modules.

The invention relates to an entity object traversal recognition detection method and device based on unmanned aerial vehicle equipment. The method comprises the following steps: acquiring cargo information acquired by unmanned aerial vehicle equipment in a cargo storage area, wherein the cargo information represents cargo storage related information acquired by the unmanned aerial vehicle equipment running according to a preset flight path and sequentially acquiring each storage position in the cargo storage area; according to the entity feature category in the cargo information, a cargo recognition algorithm matched with the cargo information is determined, cargo feature information corresponding to the cargo information is recognized based on the cargo recognition algorithm, and the cargo feature information comprises the product model, the storage number and the storage position of the corresponding cargo; and comparing the cargo feature information with inventory information in a preset database to obtain an inventory analysis result of the cargo storage area. By adopting the method, the systematic analysis of the cargo storage state can be realized, and the accuracy of inventory management and the real-time performance of information updating can be improved.

The invention belongs to the field of blend oil, relates to a data analysis technology, aims to solve the problem that an intelligent blend system for product oil in the prior art cannot perform diversified blend treatment on product oil to minimize user loss when raw materials are insufficient, and particularly relates to an intelligent blend system for product oil, which comprises a processor, the processor is in communication connection with an inventory analysis module, a reconciliation processing module, a multi-element processing module, an inventory optimization module and a storage module; the inventory analysis module is used for carrying out inventory analysis on blended component oil of the product oil: generating an analysis period and obtaining a delivery list of the analysis period, and the delivery list comprises the product oil, the blended component oil and a blending period; marking the product oil needing to be delivered in the analysis period as an analysis object; according to the method, inventory analysis can be carried out on the blended component oil of the finished oil product, whether the inventory of the blended component oil meets the requirement or not is judged according to the comparison result, and supplement early warning is carried out in time when the inventory of the blended component oil is unqualified.

A method of analyzing inventory in a diagnostic laboratory system includes capturing images of a plurality of inventory items used in the diagnostic laboratory system, wherein the capturing generates image data; analyzing the image data to identify one or more inventory items; and generating, in response to the analysis, an instruction to cause a printer to print one or more identification tags, wherein each of the one or more identification tags includes identification data identifying one of the one or more inventory items. Other methods and systems are disclosed.

AI-Based Dynamic Pricing Computer System Using Market Sentiment and Inventory Analytics

The invention discloses a steel scrap enterprise long-term immobile inventory management system and method, and belongs to the technical field of inventory management. The system comprises a long-term immobile physical inventory calculation subsystem, a long-term in-transit inventory calculation subsystem, a long-term unsettled inventory calculation subsystem, an inventory total calculation subsystem and a report generation subsystem. According to the method, the problems that long-term overstocked inventory is difficult to recognize in time and a multi-dimensional analysis view angle is lacked in traditional inventory management are solved, and a visual long-term fixed inventory analysis report is generated by automatically collecting various inventory data and performing classified calculation according to a preset rule; by establishing a hierarchical authority management system, it is ensured that the molecular companies and the head office achieve collaborative management on the premise of data isolation; the system supports the functions of drilling tracing and reason filling for long-term immobile inventory, helps enterprises to accurately locate the source of inventory backlog, optimizes the inventory structure, improves the inventory turnover efficiency, and provides data support for operation and management decisions.

The invention relates to the technical field of production scheduling, in particular to an intelligent production scheduling plan scheduling collaborative optimization system which comprises a product splitting module, an inventory analysis module, a productivity calculation module and a product marking module. The product splitting module is used for splitting the finished product into minimum manufacturing units; and the inventory analysis module is used for checking the existing material inventory according to each material required by the product and calculating the number of parts required by the target product according to a product demand calculation formula. The product can be split into minimum manufacturing units through the product splitting module, the inventory analysis module, the productivity calculation module and the product marking module; according to the method, the number of the raw materials needed by the minimum manufacturing units is calculated, meanwhile, the minimum manufacturing units can be analyzed, existing inventory is checked, and the materials which cannot be manufactured are marked, so that the production plan of all the parts is clearer, and production scheduling is more efficient.

AI-Based Dynamic Pricing Computer System Using Market Sentiment and Inventory Analytics

The invention provides a railway vehicle maintenance production management system and method, and the system comprises an assembly production line module which is used for dividing a railway vehicle maintenance production line and dynamically adjusting a maintenance production plan; the logistics transportation module is used for carrying out classification, storage, distribution and inventory analysis on installation components required by maintenance and production of the railway vehicle according to the maintenance and production plan, and generating logistics transportation information; and the data acquisition and analysis module is used for acquiring railway vehicle maintenance and production field data in real time based on the logistics transportation information, performing computer-aided analysis on the maintenance and production field data, and generating maintenance result prediction information and maintenance and production management information so as to trigger maintenance and production plan adjustment of the assembly production line module. Through system integration and intelligent management and control, reasonable allocation of maintenance resources is realized, the maintenance efficiency is improved, the operation cost is reduced, and safe and stable operation of the train is guaranteed.

According to the invention, the unsalable inventory which should be processed preferentially in the inventory can be mastered. This inventory analysis device is provided with: an inventory index value acquisition unit (12) for acquiring an inventory index value, which is an index value relating to the inventory status of a product; a sales index value acquisition unit (13) that acquires a sales index value, which is an index value relating to the sales status of the product; and an inventory recognition unit 14 that recognizes, as an unsalable inventory, a commodity inventory in which the inventory index value is evaluated to be lower than the inventory threshold value and the sales index value is evaluated to be lower than the sales threshold value. The state of the inventory is identified on the basis of a logical sum of the viewpoint and the viewpoint of whether the sales index value is evaluated to be lower than the sales threshold value, not only on the basis of the viewpoint of whether the inventory index value is evaluated to be lower than the inventory threshold value, but on the basis of the viewpoint of whether the sales index value is evaluated to be lower than the sales threshold value. A merchandise inventory in which both the inventory index value and the sales index value show low evaluation values can be grasped as an unsalable inventory to be processed preferentially in the inventory.

The invention relates to an intelligent management system for a subway carriage selling warehouse based on bidirectional coding, and discloses an intelligent management system for realizing visual display and code scanning purchase of commodity information through a commodity display terminal, and realizing accurate positioning and information tracing through establishing a bidirectional corresponding relation between commodities and warehouse spaces through a warehouse space coding module and a commodity coding module. Replenishment identification, shelf confirmation and inventory synchronization are completed through the code scanning shelf module, inventory analysis and replenishment plan generation are performed through the inventory scheduling module, and unified storage, scheduling and data management are performed through the background operation management module. Therefore, intelligent operation, accurate replenishment and efficient management of the metro carriage selling warehouse are realized. The metro carriage selling warehouse intelligent management system based on bidirectional coding is provided. The system is characterized by comprising a commodity display terminal, a storage space coding module, a commodity coding module, a code scanning and racking module, a passenger query module, an inventory scheduling module and a background operation management module.

1. Name of the product in this design: Graphical User Interface for Inventory Analysis of Electronic Devices. 2. Purpose of this design: To display the sales, inventory percentage and details of each product category in the store. 3. The key design features of this product are its graphical user interface content. 4. The image or photograph that best illustrates the design's key features: the front view. 5. Purpose of the graphical user interface: The main view interface displays the sales and inventory data of each product category and promotional series; clicking on [Ranking] displays the interface change state diagram 1 (displaying the sales and inventory amount ranking, quantity, and percentage information of the product category); clicking on [Bar] displays the interface change state diagram 2 (displaying the sales, inventory, and ranking data of each style under the corresponding product category).

The present application relates to the technical field of inventory management, and particularly relates to an inventory analysis and management optimization method of a smart pharmacy management system, comprising: acquiring a plurality of current orders, a plurality of orders in a historical time range, inventory quantities of various medicines in pharmacies, and locations of the pharmacies; acquiring a delivery cost factor of each pharmacy for each current order according to the inventory quantities of various medicines in the pharmacies and demand quantities of various medicines in the current orders, in combination with distances between each pharmacy and each current order and distances between each current order; acquiring an inventory quantity of each medicine in each pharmacy according to a quantity of orders fulfilled by each pharmacy at each location in the historical time range, and further formulating an in-out warehouse plan for each medicine in each pharmacy in combination with the delivery cost factor of each pharmacy for each current order. The present application analyzes pharmacy locations, inventory and order data, and cooperatively formulates a reasonable in-out warehouse plan for multiple pharmacies to improve medicine supply efficiency.

Systems and methods may provide for generating, maintaining, and using an inventory for insurance purposes. An optimized inventory analysis server may use a demographic classification for a given user along with data related to items owned by other users to determine one or more items for recommendation to the given user. Details associated with existing insurance coverage levels may also be used to recommend new insurance products to the user. In addition, the optimized inventory analysis server may determine a depreciated value of each item within an inventory. These values may be used to assess loss and settle an insurance claim for damage to one or more of the items in the inventory. Finally, the optimized inventory analysis server may recommend incentives on products / services sold by third party entities and may further recommend incentives on insurance products for insuring items purchased by a given user.

The invention relates to the technical field of intelligent identification, in particular to a vending cabinet commodity intelligent identification system, which comprises a data acquisition module used for acquiring commodity data, constructing commodity feature vectors, acquiring the commodity data by using a weight sensor and an image sensor according to a time sequence, and acquiring commodity feature vectors according to the acquired commodity data; constructing a commodity feature vector set of the vending cabinet at the current moment through a similarity disturbance processing mode; the commodity state judgment module is used for judging a commodity state based on the constructed commodity feature vector, performing deep analysis on the commodity feature vector through a double-layer analysis mechanism of single feature analysis and joint feature analysis, and judging the commodity state according to a deep analysis result of the commodity feature vector; and the commodity identification module is used for carrying out intelligent analysis on the commodities through an intelligent analysis mechanism according to the judgment result of the commodity state, and the intelligent analysis comprises commodity inventory analysis, sales cabinet commodity display sequence analysis and intelligent replenishment scheme analysis of the commodities.

The invention relates to the field of coal yard management, in particular to a digital coal yard automatic data acquisition system which comprises a bucket wheel machine attitude acquisition module, a bucket wheel machine position acquisition module, a granularity data acquisition module, a data transmission module, a digital map module and an inventory analysis module. The bucket wheel machine attitude acquisition module is used for acquiring bucket wheel machine attitude information in real time, and the information comprises cantilever rotation angle and pitching angle information and synchronous coal unloading belt weigher flow data, records the stacking position and quantity, and transmits the recorded data to the data transmission module. According to the invention, the data in the coal yard is collected in real time, and the data collected in real time is presented in real time through the three-dimensional map, so that workers can visually understand the equipment working parameters and the coal quantity inventory data in the coal yard, accurately carry out inventory checking, analyze the inventory change trend and formulate a reasonable purchase plan and a reasonable sales strategy; the situation of inaccurate data caused by human errors is avoided, and the management efficiency is improved.

The invention discloses a laser three-dimensional scanning system and method for real-time monitoring of greenhouse bulk material inventory. The system comprises a laser scanning unit; an environment sensing module; a weighing data acquisition module; a data processing module; a dynamic compensation and calibration module; an inventory analysis module; a feedback control unit; a communication module; volume information of a material pile is directly obtained through a laser scanning technology, the subjectivity of manual checking is overcome, and the system can sense and quantify the influence of environmental interference on a scanning result in real time by integrating various environmental sensors such as vibration, temperature and dust concentration and introducing a dynamic compensation mathematical model, so that the system is more accurate and reliable. And accurate compensation is carried out.

An e-commerce system and associated methods are provided to facilitate the cross-selling of products and services across virtual and physical stores, as well as through social media platforms. The system typically includes a store manager that allows a store owner to manage the characteristics of an e-commerce store, and a machine learning system trained to identify combinations of products that are likely to sell well together. A recommendation engine, including a store parser, inventory analysis logic, and recommendation logic, utilizes the machine learning system to generate recommendations for additional products to add to the e-commerce store based on a set of products available from external e-commerce stores and the store's current inventory. An optional product browser enables the store owner to review and select products from the generated recommendations. Methods for managing an e-commerce store and adding products to a social media feed are also disclosed, leveraging the machine learning system to enhance sales and customer engagement by recommending products based on store characteristics, social media content and customer interactions.

The application relates to a kind of entity object traversal identification detection method and device based on unmanned aerial vehicle equipment.The method comprises: obtaining the goods information collected by unmanned aerial vehicle equipment in goods storage area, and the goods information represents the information related to goods storage obtained by sequentially collecting each storage position in goods storage area according to the preset flight trajectory of unmanned aerial vehicle equipment;According to the entity feature category in goods information, determine the goods identification algorithm matched with goods information, identify the goods feature information corresponding to goods information based on goods identification algorithm, and the goods feature information includes the product model, storage quantity and storage position of corresponding goods;Compare goods feature information with inventory information in preset database, and obtain the inventory analysis result of goods storage area.The method can realize the systematic analysis of goods storage state, and help to improve the accuracy of inventory management and the real-time performance of information update.

The invention relates to the technical field of inventory management, in particular to an inventory analysis and management optimization method of an intelligent pharmacy management system, which comprises the following steps: acquiring a plurality of current orders, a plurality of orders in a historical time range, the inventory of various medicines in a pharmacy and the position of the pharmacy; according to the stock amount of each medicine in the pharmacy and the demand amount of each medicine in the current order, in combination with the distance between each pharmacy and each current order and the distance between each current order, obtaining a distribution cost factor of each pharmacy to each current order; and according to the number of orders of each pharmacy under each position within the historical time range, obtaining the warehousing amount of each medicine in each pharmacy, and further making a warehouse-out and warehouse-in plan for each medicine in each pharmacy in combination with the distribution cost factor of each pharmacy for each current order. According to the invention, by analyzing the pharmacy position, the inventory and the order data, a reasonable warehouse-in and warehouse-out plan is formulated for multiple pharmacies cooperatively, so that the medicine supply efficiency is improved.

The embodiment of the invention provides a suit analysis method and device, electronic equipment, a readable storage medium and a chip, and the method comprises the steps: receiving a natural language request for a target material; analyzing the natural language request to determine an analysis instruction related to the target material; querying and obtaining related data of the target material based on the analysis instruction; obtaining a first intelligent agent; determining an inventory analysis result corresponding to the target material according to the demand parameter and the inventory data; when it is judged that the subitem materials are in shortage according to the inventory analysis result, a second agent is obtained; acquiring at least one item of extended data related to the target material; the second intelligent agent determines at least one material shortage reason corresponding to the historical material shortage record according to the extended data; and according to the inventory analysis result and the material shortage reason, determining a neat set analysis result corresponding to the target material. Through the scheme of the invention, the time consumption of manual root cause checking by a planner is remarkably reduced, and the analysis efficiency of material set analysis is enhanced.

This invention relates to the fields of video analysis and data processing technology, and particularly to a teaching equipment management system and method based on multimodal video analysis. The system includes a dynamic weighing platform and a 3D structured light scanner for data acquisition, and synchronous output of multimodal data streams based on a precision time protocol. A feature fusion module dynamically allocates feature weight ratios through a cross-modal attention mechanism and generates lightweight device fingerprint features using a feature distillation algorithm. An identity binding module constructs a device relationship graph and achieves continuous identification and centimeter-level tracking in motion states through extended Kalman filtering and a bidirectional long short-term memory network. An inventory analysis module generates a privacy-preserving inventory report based on the identification results. This invention solves the technical problems of low efficiency in manual recording, security risks of close-range scanning, and inability to perform real-time dynamic tracking, achieving efficient and accurate management of teaching equipment through automatic accounting and intelligent inventory.

The invention discloses a fresh air purification system carbon emission accounting method based on life cycle evaluation, which is divided into five stages and establishes a quantitative model, and specifically comprises the following steps: step 1, establishing a full life cycle framework; in the step 1, five stages of raw material, production and manufacturing, transportation, use and recycling are divided, and the carbon emission source of each stage is determined. 2, determining a system boundary and accounting content; and 3, analyzing a carbon footprint list. According to the invention, the whole life cycle is covered, and accounting omission is avoided; by combining equipment parameters and actually measured data, errors are reduced, data accuracy is guaranteed, and the method is suitable for enterprise carbon auditing and product ecological design.

An e-commerce system and associated methods are provided to facilitate the cross-selling of products and services across virtual and physical stores, as well as through social media platforms. The system typically includes a store manager that allows a store owner to manage the characteristics of an e-commerce store, and a machine learning system trained to identify combinations of products that are likely to sell well together. A recommendation engine, including a store parser, inventory analysis logic, and recommendation logic, utilizes the machine learning system to generate recommendations for additional products to add to the e-commerce store based on a set of products available from external e-commerce stores and the store's current inventory. An optional product browser enables the store owner to review and select products from the generated recommendations. The system also includes storage for relevant data and a microprocessor to execute parts of the recommendation engine. Methods for managing an e-commerce store and adding products to a social media feed are also disclosed, leveraging the machine learning system to enhance sales and customer engagement by recommending products based on store characteristics, social media content, and customer interactions.

A cloud-edge collaborative dangerous chemical management method, system, device and medium are provided, and relate to the field of dangerous chemical management. In the method, a chemical compatibility risk value, an environmental out-of-control risk value, an equipment failure risk value and an operation risk value are weighted and summed to obtain a comprehensive risk value; when the comprehensive risk value is less than a preset first threshold value, a local demand prediction value is predicted, a local safety stock is calculated according to a service level and a demand fluctuation rate, a local gap value is determined according to a current inventory quantity of a first target region, the local demand prediction value and the local safety stock, and the local gap value is uploaded to the cloud; and a cross-warehouse allocation suggestion and a purchase suggestion of a target chemical are generated in the cloud according to a plurality of local gap values. By implementing the technical solution provided in the application, risk assessment and inventory analysis are performed by comprehensively considering various data, and effective management of dangerous chemicals is realized through cloud-edge collaboration.

An e-commerce system and associated methods are provided to facilitate the cross-selling of products and services across virtual and physical stores, as well as through social media platforms. The system typically includes a store manager that allows a store owner to manage the characteristics of an e-commerce store, and a machine learning system trained to identify combinations of products that are likely to sell well together. A recommendation engine, including a store parser, inventory analysis logic, and recommendation logic, utilizes the machine learning system to generate recommendations for additional products to add to the e-commerce store based on a set of products available from external e-commerce stores and the store's current inventory. An optional product browser enables the store owner to review and select products from the generated recommendations. Methods for managing an e-commerce store and adding products to a social media feed are also disclosed, leveraging the machine learning system to enhance sales and customer engagement by recommending products based on store characteristics, social media content and customer interactions.

The invention relates to the technical field of data processing, and discloses a natural resource asset checking method and system for abnormal event influence analysis. According to the method, a basic database fusing natural resource backgrounds and dynamic monitoring data is constructed, abnormal events are sensed through a multi-channel monitoring network, structural features are extracted, and a disaster stress wave propagation model is constructed and solved to generate a value loss field intensity distribution diagram. Then dividing a checking area according to the graph and intelligently scheduling investigation equipment to collect data; and finally comparing data optimization model parameters and generating a checking report. The system comprises a multi-source data fusion module, an event intelligent perception module, a stress wave deduction analysis module, an intelligent scheduling and checking module, a model optimization module and a report generation module. According to the method, the problems of low efficiency and inaccuracy of traditional evaluation are solved, and efficient and accurate checking of natural resource assets is realized.

The invention discloses a cloud-edge collaborative hazardous chemical substance management and control method, system, equipment and medium, and relates to the field of hazardous chemical substance management. In the method, a chemical compatibility risk value, an environment out-of-control risk value, an equipment failure risk value and an operation risk value are subjected to weighted summation to obtain a comprehensive risk value; when the comprehensive risk value is smaller than a preset first threshold value, predicting a local demand prediction value, calculating a local safety stock according to the service level and the demand volatility, determining a local gap value according to the current stock amount of the first target area, the local demand prediction value and the local safety stock, and uploading the local gap value to the cloud; and generating cross-library allocation suggestions and purchasing suggestions of the target chemicals at the cloud according to the plurality of local gap values. By implementing the technical scheme provided by the invention, risk assessment and inventory analysis are carried out by comprehensively considering multi-aspect data, and effective management and control of the hazardous chemical substances by cloud-side collaboration are realized.