IoCurrents has a total of 22 patents globally, out of which 8 have been granted. Of these 22 patents, more than 77% patents are active. The United States of America is where IoCurrents has filed the maximum number of patents, followed by India and Canada. Parallelly, the United States of America seems to be the main focused R&D centre and also is the origin country of IoCurrents.
IoCurrents was founded in 2015. IoCurrents creates and creates business software. The business provides fleet management, tracking, vessel monitoring, and compliance reporting systems.
Do read about some of the most popular patents of IoCurrents which have been covered by us in this article and also you can find IoCurrents patents information, the worldwide patent filing activity and its patent filing trend over the years, and many other stats over IoCurrents patent portfolio.
How many patents do the Founder and CEO of IoCurrents have?
The Founder Bhaskar Bhattacharyya, Cosmo King have 27, 16 patents and CEO Will Roberts have 8 patents.
How many patents does IoCurrents have?
IoCurrents has a total of 22 patents globally. These patents belong to 6 unique patent families. Out of 22 patents, 17 patents are active.
How Many Patents did IoCurrents File Every Year?
Are you wondering why there is a drop in patent filing for the last two years? It is because a patent application can take up to 18 months to get published. Certainly, it doesn’t suggest a decrease in the patent filing.
| Year of Patents Filing or Grant | IoCurrents Applications Filed | IoCurrents Patents Granted |
| 2022 | – | 4 |
| 2021 | 5 | 2 |
| 2020 | 12 | 2 |
| 2019 | 4 | – |
| 2017 | 1 | – |
How many IoCurrents patents are Alive/Dead?
Worldwide Patents
How Many Patents did IoCurrents File in Different Countries?
Countries in which IoCurrents Filed Patents
| Country | Patent |
| United States of America | 9 |
| India | 3 |
| Canada | 3 |
| Europe | 3 |
Where are Research Centres of IoCurrents Patents Located?
The research centres of IoCurrents Patent is United States of America.
10 Best IoCurrents Patents
US20200285997A1 is the most popular patent in the IoCurrents portfolio. It has received 104 citations so far from companies like Hailo Technologies, IBM, Adobe.
Below is the list of 10 most cited patents of IoCurrents:
| Publication Number | Citation Count |
| US20200285997A1 | 104 |
| US10650621B1 | 88 |
| US11232655B2 | 6 |
| US11216742B2 | 5 |
| CA3119273A1 | 4 |
| CA3128957A1 | 4 |
| WO2020180424A1 | 2 |
| US11200358B2 | 1 |
| US11080991B1 | 1 |
| WO2020097562A1 | 1 |
What Percentage of IoCurrents US Patent Applications were Granted?
IoCurrents (Excluding its subsidiaries) has filed 5 patent applications at USPTO so far (Excluding Design and PCT applications). Out of these 4 have been granted leading to a grant rate of 100%.
Below are the key stats of IoCurrents patent prosecution at the USPTO.
Which Law Firms Filed Most US Patents for IoCurrents?
| Law Firm | Total Applications | Success Rate |
| Seed Ip | 5 | 100% |
List of IoCurrents patents
| IoCurrents Patent | Title |
| US11468355B2 | Data Compression And Communication Using Machine Learning |
| US11328583B2 | Dynamic Gauges For Displaying Present And Predicted Machine Status |
| US11232655B2 | System And Method For Interfacing With A Vehicular Controller Area Network |
| US11216742B2 | Data Compression And Communication Using Machine Learning |
| US11200358B2 | Prediction, Planning, And Optimization Of Trip Time, Trip Cost, And/Or Pollutant Emission For A Vehicle Using Machine Learning |
| US11080991B1 | Dynamic Gauges For Displaying Present And Predicted Machine Status |
| US10803213B2 | Prediction, Planning, And Optimization Of Trip Time, Trip Cost, And/Or Pollutant Emission For A Vehicle Using Machine Learning |
| US10650621B1 | Interfacing With A Vehicular Controller Area Network |
| US20200285997A1 | Near Real-Time Detection And Classification Of Machine Anomalies Using Machine Learning And Artificial Intelligence |
| EP3935581A4 | Data Compression And Communication Using Machine Learning |
| EP3935507A4 | Near Real-Time Detection And Classification Of Machine Anomalies Using Machine Learning And Artificial Intelligence |
| EP3877235A1 | Machine Learning-Based Prediction, Planning, And Optimization Of Trip Time, Trip Cost, And/Or Pollutant Emission During Navigation |
| WO2021242224A1 | Dynamic Gauges For Displaying Present And Predicted Machine Status |
| WO2020180887A1 | Near Real-Time Detection And Classification Of Machine Anomalies Using Machine Learning And Artificial Intelligence |
| WO2020180424A1 | Data Compression And Communication Using Machine Learning |
| WO2020097562A1 | Machine Learning-Based Prediction, Planning, And Optimization Of Trip Time, Trip Cost, And/Or Pollutant Emission During Navigation |
| IN202117040418A | Near Real-Time Detection And Classification Of Machine Anomalies Using Machine Learning And Artificial Intelligence |
| IN202117040421A | Data Compression And Communication Using Machine Learning |
| IN202117024649A | Machine Learning-Based Prediction, Planning, And Optimization Of Trip Time, Trip Cost, And/Or Pollutant Emission During Navigation |
| CA3128973A1 | Data Compression And Communication Using Machine Learning |
| CA3119273A1 | Machine Learning-Based Prediction, Planning, And Optimization Of Trip Time, Trip Cost, And/Or Pollutant Emission During Navigation |
| CA3128957A1 | Near Real-Time Detection And Classification Of Machine Anomalies Using Machine Learning And Artificial Intelligence |