Abstract: A method and system for providing more relevant search results and recommendation from a food database is disclosed. The method includes receiving a query, a first candidate food, and a second candidate food. The method includes generating vectors based on the query and food names of the first and second candidate foods using at least one embedding function of a machine learning model. The method includes determining nutrition content vectors from the nutritional data of the first and second candidate foods. The method includes generating a nutrition content vector based on the query using another embedding function of the machine learning model. The method includes determining which of the first and second candidate food is more relevant to the query based at least in part on the nutrition content vectors. The method includes providing search results or recommendation based on the determined relevance.

Abstract: Methods and systems of enabling a transportation mode on a telematics device couplable to a vehicle are provided. A method includes detecting a first event or receiving a command for enabling a transportation mode, running a transportation mode power-saving scheme in response to receiving the first event or the command, and exiting the transportation mode power-saving scheme in response to detecting a second event.

Abstract: A health tracking system and method of operation is disclosed herein. The method of operating the health tracking system comprises: receiving a first data record comprising at least a first descriptive string regarding a consumable item, the first descriptive string having at least one word thereof incorrectly spelled; generating a vector using the first descriptive string using a machine learning model; identifying a second descriptive string which corresponds to the consumable item and which has a correct spelling of the at least one incorrectly spelled word by applying the machine learning model to the generated vector; calculating a confidence factor regarding the identified second descriptive string using the machine learning model; and when it is determined that the confidence factor exceeds a predetermined threshold, (i) modifying the first data record by replacing the first descriptive string with the second descriptive string, and (ii) storing the modified first data record in the database.

Abstract: Methods, systems, and devices for asset travel monitoring are provided. An example method for asset travel monitoring involves monitoring a motion sensor of an asset tracking device located at an asset to determine whether the asset has entered into a travelling state, upon determination that the asset has entered into the travelling state, monitoring the motion sensor to determine whether the asset has left the travelling state, and, upon determination that the asset has left the travelling state, obtaining a present location of the asset tracking device and transmitting the present location to a remote server.

Abstract: A method of operating a health tracking system is disclosed. The method comprises: receiving a first data record comprising at least a first descriptive string regarding a consumable item, the first descriptive string having at least one word thereof incorrectly spelled; generating a vector using the first descriptive string using a machine learning model; identifying a second descriptive string which corresponds to the consumable item and which has a correct spelling of the at least one incorrectly spelled word by applying the machine learning model to the generated vector; calculating a confidence factor regarding the identified second descriptive string using the machine learning model; and when it is determined that the confidence factor exceeds a predetermined threshold, (i) modifying the first data record by replacing the first descriptive string with the second descriptive string, and (ii) storing the modified first data record in the database.

Abstract: Methods and systems of enabling a storage mode on a telematics device coupled to a vehicle are provided. One method includes detecting a first event or receiving a command for enabling a storage mode, entering the storage mode in which the telematics device is in a sleep mode in response to receiving the first event or the command, and exiting the storage mode in response to detecting a second event.

Abstract: Methods and systems of enabling a transportation mode on a telematics device coupled to a vehicle are provided. One method includes detecting a first event or receiving a command for enabling a transportation mode, running a transportation mode power-saving scheme in response to receiving the first event or the command, and exiting the transportation mode power-saving scheme in response to detecting a second event.

Abstract: Methods, systems, and devices for temperature-dependent charging of supercapacitor energy storage units of asset tracking devices are provided. An example method for temperature-dependent charging involves obtaining a temperature reading measured at an asset tracking device, the asset tracking device located at an asset to monitor travel of the asset, determining a target voltage for a supercapacitor energy storage unit of the asset tracking device based on the temperature reading to balance utilization of a capacity of the supercapacitor energy storage unit against temperature-dependent deterioration of the supercapacitor energy storage unit, and controlling a charging interface of the asset tracking device to charge the supercapacitor energy storage unit to the target voltage.

Abstract: Apparatus and methods are given for providing enhanced product recommendations. In one embodiment, products are recommended to a consumer based on information manually entered by the consumer and/or derived from data relating to the consumer obtained from a health-monitoring platform. The recommended products are provided from a recommendation engine to a human operator or curator at an item selection entity, the curator selects a predetermined number of the recommended products for delivery to the consumer. Such delivery is established by the consumer to occur periodically (such as monthly) as part of a subscription service. Product recommendations are adjusted over time to relate to customer activity and interest data accumulated from the health-monitoring platform. In one embodiment, a recommendation engine is configured to specifically tailor its recommendation algorithms based on feedback information received from the curator and/or the consumer.

Abstract: System and method for associating user-entered consumable item description to an entry in a consumable item database. In one embodiment, formally structured restaurant menu item is matched to a large database of food items that has been constructed via crowd-sourcing. A novel, practical, and scalable machine learning solution architecture, consisting of two major steps is utilized. First a query generation approach is applied, based on a Markov Decision Process algorithm, to reduce the time complexity of searching for matching candidates. That is then followed by a re-ranking step, using deep learning techniques, to ensure matching quality goals are met.

Abstract: Apparatus and methods are given for providing enhanced product recommendations. In one embodiment, products are recommended to a consumer based on information manually entered by the consumer and/or derived from data relating to the consumer obtained from a health-monitoring platform. The recommended products are provided from a recommendation engine to a human operator or curator at an item selection entity, the curator selects a predetermined number of the recommended products for delivery to the consumer. Such delivery is established by the consumer to occur periodically (such as monthly) as part of a subscription service. Product recommendations are adjusted over time to relate to customer activity and interest data accumulated from the health-monitoring platform. In one embodiment, a recommendation engine is configured to specifically tailor its recommendation algorithms based on feedback information received from the curator and/or the consumer.

Abstract: System and method for associating user-entered consumable item description to an entry in a consumable item database. In one embodiment, formally structured restaurant menu item is matched to a large database of food items that has been constructed via crowd-sourcing. A novel, practical, and scalable machine learning solution architecture, consisting of two major steps is utilized. First a query generation approach is applied, based on a Markov Decision Process algorithm, to reduce the time complexity of searching for matching candidates. That is then followed by a re-ranking step, using deep learning techniques, to ensure matching quality goals are met.

Abstract: A method and system for providing more relevant search results and recommendation from a food database is disclosed. The method includes receiving a query, a first candidate food, and a second candidate food. The method includes generating vectors based on the query and food names of the first and second candidate foods using at least one embedding function of a machine learning model. The method includes determining nutrition content vectors from the nutritional data of the first and second candidate foods. The method includes generating a nutrition content vector based on the query using another embedding function of the machine learning model. The method includes determining which of the first and second candidate food is more relevant to the query based at least in part on the nutrition content vectors. The method includes providing search results or recommendation based on the determined relevance.

Abstract: A method of operating a health tracking system is disclosed. The method comprises: receiving a first data record comprising at least a first descriptive string regarding a consumable item, the first descriptive string having at least one word thereof incorrectly spelled; generating a vector using the first descriptive string using a machine learning model; identifying a second descriptive string which corresponds to the consumable item and which has a correct spelling of the at least one incorrectly spelled word by applying the machine learning model to the generated vector; calculating a confidence factor regarding the identified second descriptive string using the machine learning model; and when it is determined that the confidence factor exceeds a predetermined threshold, (i) modifying the first data record by replacing the first descriptive string with the second descriptive string, and (ii) storing the modified first data record in the database.

Abstract: Methods, systems, and devices for temperature-dependent charging of supercapacitor energy storage units of asset tracking devices are provided. An example method for temperature-dependent charging involves obtaining a temperature reading measured at an asset tracking device, the asset tracking device located at an asset to monitor travel of the asset, determining a target voltage for a supercapacitor energy storage unit of the asset tracking device based on the temperature reading to balance utilization of a capacity of the supercapacitor energy storage unit against temperature-dependent deterioration of the supercapacitor energy storage unit, and controlling a charging interface of the asset tracking device to charge the supercapacitor energy storage unit to the target voltage.

Abstract: Methods, systems, and devices for monitoring asset tracking devices that travel together are provided. An example method for monitoring asset tracking devices that travel together involves obtaining a first travel history of a first asset tracking device, obtaining a second travel history of a second asset tracking device, determining, based on the first and second travel histories, whether the first asset tracking device and the second asset tracking device travel together, and, upon determination that the first asset tracking device and the second asset tracking device travel together, linking the first asset tracking device and the second asset tracking device together in an asset tracking database to indicate that the first asset tracking device and the second asset tracking device travel together.

Abstract: Methods, systems, and devices for asset travel monitoring are provided. An example method for asset travel monitoring involves monitoring a motion sensor of an asset tracking device located at an asset to determine whether the asset has entered into a travelling state, upon determination that the asset has entered into the travelling state, monitoring the motion sensor to determine whether the asset has left the travelling state, and, upon determination that the asset has left the travelling state, obtaining a present location of the asset tracking device and transmitting the present location to a remote server.

Abstract: A method and system for providing more relevant search results and recommendation from a food database is disclosed. The method includes receiving a query, a first candidate food, and a second candidate food. The method includes generating text feature vectors based on the query and food names of the first and second candidate foods using at least one first embedding function of a machine learning model. The method includes determining nutrition content vectors from the nutritional data of the first and second candidate foods. The method includes generating a nutrition content vector based on the query using a second embedding function of the machine learning model. The method includes determining which of the first and second candidate food is more relevant to the query based on the text feature vectors and the nutrition content vectors. The method includes providing search results or recommendation based on the determined relevance.

Abstract: A method of operating a health tracking system is disclosed. The method comprises: receiving a first data record comprising at least a first descriptive string regarding a consumable item, the first descriptive string having at least one word thereof incorrectly spelled; generating a vector using the first descriptive string using a machine learning model; identifying a second descriptive string which corresponds to the consumable item and which has a correct spelling of the at least one incorrectly spelled word by applying the machine learning model to the generated vector; calculating a confidence factor regarding the identified second descriptive string using the machine learning model; and when it is determined that the confidence factor exceeds a predetermined threshold, (i) modifying the first data record by replacing the first descriptive string with the second descriptive string, and (ii) storing the modified first data record in the database.

Abstract: A method for operating a health tracking system, a health tracking system, and non-transitory computer-readable medium for operating a health tracking system are disclosed. The method comprises receiving a data record comprising at least a descriptive string and nutritional data regarding a consumable item to which the data record corresponds; determining a taste associated to the consumable item based on an evaluation of at least one of: (i) the descriptive string, and (ii) the nutritional data; and associating the determined taste with the data record in a database.