PATENT CLAIM ANALYSIS

Application Number: 16072870
Application Type: Utility
Filing Date: 2018-07
Publication Date: 2018-12
Patent Classification: ["340", "573100"]

Abstract:
A system for monitoring and private assistance to people includes sensors that detect descriptive parameters of environmental conditions, and sensors and/or devices that monitor a person's position and, optionally, her physiological parameters. In particular, the system includes sensors and/or devices that monitor a person's position at the topological level and generate tracking signals in time and within a digital topological model of the environment; sensors that monitor posture and/or its variations in time and that provide status signals corresponding to predetermined postures and/or signals, indicating posture variations in time, which are processed by a logic control unit and software that evaluates position and posture and its variation in time and that classifies the signals according to predetermined categories of motor and/or postural activities, and that performs a comparison between detected parameters and predefined patterns of execution.

Claim (Index 9):
The system according to  claim 1 , wherein the system comprises a modular and scalable architecture with four levels, which comprise:\n i. a layer consists of a hardware infrastructure; ii. a layer consists of the classification algorithm, executed on the hardware infrastructure, which implements both a classification procedure based on a taxonomic data structure and a dialogue with the monitored person; and iii. a layer constituted by a data structure containing symbols representing models, normative behavioural patterns, symbols which describe some characteristics of an environment, or symbols which refer to possible dialogues described in a logical formalism based on description logics; wherein a data structure includes: a. models that connect sensory data to the symbols, combinations of the symbols or temporal sequences of the symbols that refer to actions executed by the monitored person and the postures of the monitored person; b. models that connect the sensory data to the symbols, the combinations of the symbols, or the temporal sequences of the symbols that refer to typical habits of the monitored person; c. a model that represents the environment in which the monitored person lives and acts, based on characteristics thereof using the symbols, the combinations of the symbols, or the temporal sequences of the symbols, for localization of the monitored person at topological level; d. models that encode normative aspects related to healthy habits for a the monitored person by the symbols, the combinations of the symbols, or the temporal sequences of the symbols, to define whether the symbols, the combinations of the symbols, or the temporal sequences of the symbols representing the data from the first and the second sensors correspond to potentially dangerous situations or to bad habits of the monitored person; e. rule-based models that based on a classification of the symbols, the combinations of the symbols, or the temporal sequences of the symbols generate alarms or messages, or receive feedback for dialogues with the monitored person; and f. models related to rules or based on structures related to formal grammars for encoding dialogues with the monitored person using the symbols the combinations of the symbols, or temporal sequences of the symbols; and iv. a layer of communication and sharing of the data among system hardware devices and with external communication systems; further comprising a communication network that uses standard open protocols for interfacing with all the hardware components of the system.

Metadata:
- Claim Count in Document: 23.0
- Percentile: 95.0
- Lexical Diversity: 1.89744
- Patent Class: 340.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: True
- Related Applications: ['15562751', '09808848', '10678773', '14128574', '15276804']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.6403657477343071
- 35 USC 102 Novelty (BERT): 0.507739132125203
- Combined Prediction Score: 0.6271030861733967
- Mean Citation Score: 112.61811000000002
- Max Citation Score: 130.41971
- Similarity Product: 69.60179510232688

Labels:
- Claim Label 101: 1
- Claim Label 102: 1
- Claim Label 103: 1
- Claim Label 112: 0
- Combined Label: 1
- Label 101 Adjusted: 1

Dataset: test