Prosecution Insights
Prosecution Insights
Technology areas: Networking & Security • Communications • Transportation, E-Commerce & Mechanical Systems
7 pending office actions • 4 art units • 7 examiners • 0 of 7 (0%) have an AI response strategy ready • 19 patents granted in the last 365 days
ObjectVideo Labs LLC has 7 pending office actions in the Communications technology area. These actions are distributed among 7 distinct examiners and 4 distinct art units. This indicates that each pending action is being reviewed by a different examiner. The 4 distinct art units involved suggest that the company's communications innovations are being evaluated by several different specialized groups within the USPTO. This distribution requires a strategy that can address the specific requirements of multiple examination divisions.
The busiest examiner, LI, TRACY Y, has 1 pending action. This matches the distribution where 7 distinct examiners handle the 7 total pending office actions. With 7 distinct examiners and 4 distinct art units, the portfolio is decentralized across multiple individuals. Practitioners should be prepared to address the specific requirements of 4 different art units while managing 7 separate examiner relationships in the Communications technology area. The lack of examiner overlap means each case will likely proceed on its own unique timeline and technical merits.
Based on the USPTO statutory response window for each pending office action. 1 of the docket's apps have a known mailing date; the rest are excluded from the tile counts.
Difficulty is derived from the rejection statutes on the most recent pending office action. §101-driven and multi-statute cases are graded Hard; §112-only and obviousness-type double-patenting cases are graded Easy; everything else is Medium. "Unknown" means we have not yet parsed a statute for that office action.
| Bucket | Cases |
|---|---|
| §101 + other | 3 (43%) |
| §103 only | 3 (43%) |
| Double-patenting only | 1 (14%) |
How the docket's pending cases split across USPTO tech-center bands.
Manual office-action response work runs about 10 hours per case. The time-saved bands below show what IP Author's prosecution pipeline typically delivers — a conservative 20% on the low end, 35% in the middle, 50% on the high end.
| Examiner | Apps on this docket | Allow rate | Interview lift |
|---|---|---|---|
| LI, TRACY Y | 1 | 80.6% | +16.1% |
| ALIZADA, OMEED | 1 | 77.4% | +32.7% |
| GAMMON, MATTHEW CHRISTOPHER | 1 | 68.4% | +21.0% |
| HONG, DUNG | 1 | 83.8% | +14.2% |
| SATTI, HUMAM M | 1 | 63.6% | +17.9% |
| CAI, PHUONG HAU | 1 | 76.9% | +26.4% |
| HAO, YI | 1 | 34.0% | +46.4% |
Cases in front of an examiner with an allow rate of 80%+ where the difficulty is Easy or Medium. The top 1 ordered by deadline are shown.
| App # | Title | Examiner | Due in |
|---|---|---|---|
| 18920005 | MONITORING STANDING WATER AND DRAINAGE PROBLEMS | HONG, DUNG | — |
Multi-statute / §101-driven matters, or cases in front of an examiner with an allow rate under 30%. The top 3 ordered by deadline are shown.
| App # | Title | Examiner | Due in |
|---|---|---|---|
| 19303938 | USING IMPLICIT EVENT GROUND TRUTH FOR VIDEO CAMERAS | LI, TRACY Y | — |
| 19024291 | ROBOT FLOORPLAN NAVIGATION | GAMMON, MATTHEW CHRISTOPHER | — |
| 18208675 | MONITORING SYSTEM RULE GENERATION | HAO, YI | — |
Cases in front of an examiner whose interview lift is 10 percentage points or more — i.e. interviewed cases historically resolve more favorably than non-interviewed ones. The top 7 ordered by deadline are shown.
| App # | Title | Examiner | Due in |
|---|---|---|---|
| 18654391 | ADJUSTING AREAS OF INTEREST FOR MOTION DETECTION IN CAMERA SCENES | SATTI, HUMAM M | 34d |
| 19303938 | USING IMPLICIT EVENT GROUND TRUTH FOR VIDEO CAMERAS | LI, TRACY Y | — |
| 19227621 | NETWORK DEVICE EVENT PROCESSING | ALIZADA, OMEED | — |
| 19024291 | ROBOT FLOORPLAN NAVIGATION | GAMMON, MATTHEW CHRISTOPHER | — |
| 18920005 | MONITORING STANDING WATER AND DRAINAGE PROBLEMS | HONG, DUNG | — |
| 18220330 | OBJECT EMBEDDING LEARNING | CAI, PHUONG HAU | — |
| 18208675 | MONITORING SYSTEM RULE GENERATION | HAO, YI | — |
| Art Unit | Apps |
|---|---|
| 2686 | 1 |
| 3657 | 1 |
| 2422 | 1 |
| 2673 | 1 |
| App # | Title | Examiner | Art Unit | Statutes | Status | Due in | AI | Filed |
|---|---|---|---|---|---|---|---|---|
| 19303938 | USING IMPLICIT EVENT GROUND TRUTH FOR VIDEO CAMERAS | LI, TRACY Y | — | §101§103§112 | Non-Final OA | — | Pending | Aug 19, 2025 |
| 19227621 | NETWORK DEVICE EVENT PROCESSING | ALIZADA, OMEED | 2686 | §103 | Non-Final OA | — | Pending | Jun 04, 2025 |
| 19024291 | ROBOT FLOORPLAN NAVIGATION | GAMMON, MATTHEW CHRISTOPHER | 3657 | §101§103§112 | Final Rejection | — | Pending | Jan 16, 2025 |
| 18920005 | MONITORING STANDING WATER AND DRAINAGE PROBLEMS | HONG, DUNG | — | DP | Non-Final OA | — | Pending | Oct 18, 2024 |
| 18654391 | ADJUSTING AREAS OF INTEREST FOR MOTION DETECTION IN CAMERA SCENES | SATTI, HUMAM M | 2422 | §103 | Non-Final OA | 34d | Pending | May 03, 2024 |
| 18220330 | OBJECT EMBEDDING LEARNING | CAI, PHUONG HAU | 2673 | §103 | Non-Final OA | — | Pending | Jul 11, 2023 |
| 18208675 | MONITORING SYSTEM RULE GENERATION | HAO, YI | — | §101§102§103 | Non-Final OA | — | Pending | Jun 12, 2023 |
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