eScent
PERSONALISED SCENT BUBBLE
PATENTS
Intro
Our patent portfolio is a combination of patents covering the broad uses of wearable scent technologies and associated applications for personalised scent release, triggered by sound and/or biometric properties, new techniques for creating a scent dispersal sphere around the body dependent upon user context, music data, environment, activity data, etc, and some techniques employing machine learning.
This page lists patents which are either granted or are pending. In addition, we maintain trade secrets and know-how around Dr Jenny Tillotson's award-winning 'Scentsory Design' research which has been built up from years of practical experience, including work at Central Saint Martins, University of Cambridge and the Royal College of Art.
AWARDED PATENTS
A system and method for dispensing fluid in response to a sensed property" (GB)
The present invention relates to a wearable system and method for dispensing fluid in response to a sensed property, such as a biometric property of an individual or various sounds. Details methods to dispense liquids around fabrics
"A system and method for dispensing fluid in response to a sensed property" (China)
"A system and method for dispensing fluid in response to a sensed property" (USA)
"A system and method for dispensing fluid in response to a sensed property" (USA continuation patent)
Awarded 15th October 2019
PENDING PATENTS
GB patent application filed 29.7.2017 (Priority date)
"Scent bubble personalised scent dispersal system from wearable items"
PCT filed July 2018
(PCT/GB2018/052097)
"Liquid dispensing system creating and maintaining a personalised bubble with a defined radius and concentration"
The PCT was published on 7 February 2019 under no. WO 2019/025763
New techniques for personalised scent dispersal, which with a modest scent reservoir allow use without recharge for a period of weeks to months or even years. Also techniques for therapeutic scent dispersal. Further, techniques for dispensing scent dependent upon user context/environment, music data, weather, calendar, activity data, etc. Some of the techniques may employ machine learning.
Applications filed in: