DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Priority
The ADS is claiming foreign priority application 202110916736.3. However, said application is filed more than 12/6 months from the instant application under examination. The PCT missing a country code, “CN”, from the application number made the foreign priority claim improper.
Allowable Subject Matter
Applicant is advised that the Notice of Allowance mailed September 3, 2025 is vacated. If the issue fee has already been paid, applicant may request a refund or request that the fee be credited to a deposit account. However, applicant may wait until the application is either found allowable or held abandoned. If allowed, upon receipt of a new Notice of Allowance, applicant may request that the previously submitted issue fee be applied. If abandoned, applicant may request refund or credit to a specified Deposit Account.
Prosecution on the merits of this application is reopened on claims 1-8 considered unpatentable for the reasons indicated below.
The indicated allowability of claims 1-8 is withdrawn in view of the newly discovered reference to Wang et al. (CN 113625352 A). Rejections based on the newly cited reference follow.
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claims 1-8 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Wang et al.
Wang et al. discloses a city underground space resistivity sensing system and data collecting method based on cloud edge end cooperation comprising:
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With regard to claim 1, an urban underground space resistivity sensing system based on cloud-edge-end collaboration, wherein the system adopts a cloud-edge-end architecture design comprising a central cloud computing platform, a plurality of edge servers connected to the central cloud computing platform through a distributed network, and a plurality of resistivity sensing nodes connected to each edge server through a distributed network; the central cloud computing platform is configured to manage the entire resistivity sensing system, comprising: setting up and configuring distributed edge servers, managing all resistivity sensing nodes through edge servers; conducting overall data processing and model inversion, comprising: comparing and analyzing real-time data and historical data, sending model results to the edge servers to guide preliminary data analysis; and issuing alerts and reports for data exceeding thresholds; the edge server, serving as an edge node, is responsible for coordinating the collaborative work of multiple resistivity sensing nodes within a controlled domain of the edge server, comprising: coordinating and controlling a selection and collection process of power supply and potential measurement electrode pairs within the control domain; filtering, organizing, and storing the collected data within the control domain in a designed format, simultaneously uploading the data to the central cloud computing platform for backup; after completing data collection, comparing and analyzing real-time data, historical data, and the model calculation results for the region fed back by the central cloud computing platform based on historical data to detect anomalies; if anomalies are detected, reporting, by the edge server, the abnormal information to the central cloud computing platform; the resistivity sensing node, serving as an end node, is horizontally placed along city roads and/or vertically placed in wellbores; each resistivity sensing node is an independent resistivity sensor unit, including a data collection station, a multi-channel electrode conversion switch connected to the data collection station, a multi-core electrical resistivity tomography (ERT)cable, and a grounding electrode connected to the multi-core ERT cable; the power supply or potential measurement tasks are performed by the resistivity sensing node according to the instructions of the edge node associated with the resistivity sensing node, and the measurement data is uploaded by the resistivity sensing node to the corresponding edge node (Claim 1).
With regard to claim 2, when resistivity sensing nodes are horizontally placed along city roads, the cables in the resistivity sensing nodes are multi-core segmented cascaded ERT cables; the segmented cascaded cables are serially connected into a single cable through a cascaded electrode conversion switch, with the data collection station connected to one end of the complete cable; when the resistivity sensing nodes are vertically placed in wellbores, the cables in the resistivity sensing nodes are single centralized high-density electrical cables in which a plurality of electrode structures are evenly spaced; each electrode structure serves as a grounding electrode, and the top of the cable is connected to the data collection station through a centralized electrode switch; when the resistivity sensing nodes are placed both horizontally along city roads and in wellbores, the single centralized high-density electrical cable in the wellbore is first connected to one end of the multi-core segmented cascaded high-density electrical cable on the ground through a centralized electrode conversion switch; the data collection station is connected to the other end of the segmented cascaded ERT cable; a plurality of electrode structures are evenly spaced on the centralized ERT cable, each serving as a grounding electrode (Claim 2).
With regard to claim 3, the data collection station comprises a control module, a power supply module, a potential measurement module, a communication module, and a GPS module; the control module, under the command of the associated edge node, is configured to manage the operation of the data collection station's system, including self-management, self-checking, communication with edge nodes, functional interchange between power supply and potential measurement under control of collection instructions, channel selection, execution of the collection process, and data storage and upload of measurement data; the power supply module, upon receiving a power supply command, is configured to select the corresponding electrode channel through the control module, supply power to the underground through the connected cable channel and electrodes, measure the power supply current magnitude, and upload the node's and power supply channel's identification, measurement start time, and power supply current value after completing the power supply; the potential measurement module, upon receiving a potential measurement command, is configured to select the corresponding electrode channel through the control module, perform potential measurement through the connected cable channel and electrodes, and measure the potential difference, and upload the node's and potential measurement channel's identification, measurement start time, and potential difference value; the GPS module is configured for precise time synchronization and coordination of all nodes (Claim 3).
With regard to claim 4, the edge nodes is communicated remotely with end nodes through a mobile communication network, and the edge nodes is communicated remotely with the central cloud computing platform through a wired network (Claim 4).
With regard to claim 5, a method for collecting urban underground space resistivity data based on cloud-edge-end collaboration, wherein the method is implemented by the system of claim 1, comprising the following steps: (1) determining an arrangement and collection parameters of resistivity sensing nodes based on actual conditions of a target street, a maximum exploration depth, and a resolution of underground detection targets; (2) arranging the resistivity sensing nodes on the target street; a unique system identification is assigned, by the central cloud computing platform, to each edge node, and a unique system identification is assigned, by each edge node, to each resistivity sensing node within the domain of the edge node; a unique system identification is assigned, by the sensing node, to each electrode point in the sensing node; collecting three-dimensional geographic coordinates of each electrode point; (3) sequentially selecting, by the central cloud computing platform, different edge nodes for block measurements; the selected edge node, in sequence according to the system identification of resistivity sensing nodes; selecting one sensing node as a power supply node, and then selecting one electrode combination within the sensing node as a power supply electrode pair AB, and selecting an electrode combination within the domain of the edge node belonging to the sensing node as a potential measurement electrode pair MN; wherein the potential measurement electrode pair MN belongs to a same sensing node; determining whether a distance between the measurement electrode pairs MN and AB is within an effective measurement radius r of AB; if yes, performing power supply and potential measurement; if no, moving to the next ABMN combination position for a new measurement condition judgment; the effective measurement radius of AB is given by r ≤ n.a, where n is the effective radius coefficient, n=6−14, and a is the distance between A and B; traversing all power supply electrode pairs and the plurality of paired potential measurement electrode pairs within the sensing node, and completing the power supply and potential measurement process when the sensing node acts as the power supply node; (4) sequentially moving to the next resistivity sensing node and performing the power supply and potential measurement process until all power supply electrode combinations for the last sensing node are completed, thereby finishing the entire power supply and potential measurement process for the current edge node; (5) proceeding to the next edge node and performing the same power supply and potential measurement process until all edge nodes have been traversed. (6) after completing the data collection, the edge node is configured to notify each sensing node to upload the collected data and its own status information; the edge node is configured to format the data within the domain, quickly compare the data with the region model results downloaded from the central cloud computing platform, and provide processing analysis results; the edge node is configured to report the preliminary processing and analysis results to the central cloud computing platform; the central cloud computing platform, based on historical data and intelligent analysis model results from other sources, is configured to feedback and distribute the results to each edge node to guide subsequent edge nodes in rapid anomaly analysis and risk identification (Claim 5).
With regard to claim 6, when AB serves as the power supply electrode pair, and the GPS module is configured to coordinate timed parallel measurement of potential measurement electrode pair MN which is positioned different nodes and satisfies conditions, namely, multiple potential measurement electrode pairs MN at different nodes parallelly work with one power supply electrode pair AB, and thus achieving One-Supply Multiple-Measurements simultaneously (Claim 6).
With regard to claim 7, when selecting the power supply electrode pair AB, follow the principle of increasing electrode numbers and start from the end where the collection station is located; selecting the electrode A as the closest electrode point to the collection station, and selecting the electrode B with a sequence number interval of 1 as the power supply electrode pair AB; maintaining the sequence number interval of AB, shifting A and B to the next electrode point until point B reaches the last electrode point of the current sensing nodes, and completing all power supply processes with AB sequence number interval equal to 1; starting from the beginning and select points A and B with a sequence number interval of 2 for power supply; shifting A and B until point B reaches the last electrode point, and completing the power supply process with a sequence number interval of 2 between A and B; and repeating to change the interval between A and B until the set maximum isolation coefficient is reached, completing the power supply process for that sensing node (Claim 7).
With regard to claim 8, once the resistivity sensing nodes are arranged, and the positions of each electrode point are fixed with accurate coordinates, the corresponding edge node calculates and creates a power supply and potential measurement collection table in advance; the table orderly comprises a sensing node number and an electrode number of each power supply point AB, as well as the sensing node number and electrode number of the plurality of potential measurement points MN, ensuring that the actual collection is executed in the order of the table, and completing the entire data collection process (Claim 8).
CONTACT INFORMATION
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HOAI-AN D. NGUYEN
Primary Examiner
Art Unit 2858
/HOAI-AN D. NGUYEN/ Primary Examiner, Art Unit 2858