Daniel Siddall

Title: Innovations by Daniel Siddall

Introduction

Daniel Siddall is an accomplished inventor based in Boise, ID (US). He has made significant contributions to the field of technology, particularly in the area of predictive maintenance for printing devices. His innovative approach utilizes advanced algorithms to enhance the reliability of such devices.

Latest Patents

One of Siddall's notable patents is titled "Part replacement predictions using convolutional neural networks." This invention includes an apparatus with a communication interface that receives an image file representing a scanned output generated by a printing device. The apparatus features an identification engine that processes the image file using a convolutional neural network model to identify features indicative of potential failures. Additionally, it includes an image analysis engine that determines the life expectancy of a part associated with the potential failure based on the identified feature. This innovative use of convolutional neural networks allows for more accurate predictions regarding part replacements, ultimately improving device performance and reducing downtime. Siddall holds 1 patent.

Career Highlights

Throughout his career, Daniel Siddall has worked with prominent organizations, including Hewlett-Packard Development Company, L.P. and the Rochester Institute of Technology. His experience in these institutions has allowed him to refine his skills and contribute to various technological advancements.

Collaborations

Siddall has collaborated with notable colleagues such as Darrel D. Cherry and Renee Jeanette Jessome. These partnerships have fostered a creative environment that has led to innovative solutions in their respective fields.

Conclusion

Daniel Siddall's contributions to technology, particularly through his patent on predictive maintenance, showcase his innovative spirit and dedication to improving device reliability. His work continues to influence the industry and inspire future advancements.