Techniques are described that combine machine learning with an edge network that includes IoT devices to yield an effective and efficient method of assessing a condition of an environment. An inference module that includes a machine-learning algorithm, installed and executing on the IoT devices, assesses a condition detected from multiple, different geographic locations. The IoT devices transfer sets of data and inferences as well as respective sets of confidence levels to converge on a verified set of inferences. The verified set of inferences is arrived at quickly and with a high confidence level
Machine learning systems (MLSys) are emerging in the Internet of Things (IoT) to provision edge inte...
INST: L_042Edge computing is an essential technology to enable machine learning capabilities on IoT ...
Machine learning is one of the emerging technologies that has grabbed the attention of academicians ...
The Internet of Things (IoT) offers the ability to analyze and predict our surroundings through sen...
Smart devices continue to proliferate as the Internet-of-Things expands. Collectively, Internet-of-...
Rapid growth in numbers of connected devices, including sensors, mobile, wearable, and other Interne...
The role that the real-time inference model plays in the Internet of Things environment and the appl...
Machine learning employs computational methods from advanced analytics that use statistical algorith...
Right now, the dominant paradigm to supportknowledge extraction from raw IoT data is through global ...
Rapid growth in numbers of connected devices including sensors, mobile, wearable, and other Internet...
In the era of big data and Internet-of-Things (IoT), ubiquitous smart devices continuously sense the...
With the increasing ubiquity of edge devices, such as the Internet of Things (IoT) and mobile device...
The rapid development in ubiquitous computing has enabled the use of microcontrollers as edge device...
With the coming of fast advancements, with the assistance of IoT, a great percentage of heterogeneou...
The data that medical sensors collect can be overwhelming, making it challenging to glean the most r...
Machine learning systems (MLSys) are emerging in the Internet of Things (IoT) to provision edge inte...
INST: L_042Edge computing is an essential technology to enable machine learning capabilities on IoT ...
Machine learning is one of the emerging technologies that has grabbed the attention of academicians ...
The Internet of Things (IoT) offers the ability to analyze and predict our surroundings through sen...
Smart devices continue to proliferate as the Internet-of-Things expands. Collectively, Internet-of-...
Rapid growth in numbers of connected devices, including sensors, mobile, wearable, and other Interne...
The role that the real-time inference model plays in the Internet of Things environment and the appl...
Machine learning employs computational methods from advanced analytics that use statistical algorith...
Right now, the dominant paradigm to supportknowledge extraction from raw IoT data is through global ...
Rapid growth in numbers of connected devices including sensors, mobile, wearable, and other Internet...
In the era of big data and Internet-of-Things (IoT), ubiquitous smart devices continuously sense the...
With the increasing ubiquity of edge devices, such as the Internet of Things (IoT) and mobile device...
The rapid development in ubiquitous computing has enabled the use of microcontrollers as edge device...
With the coming of fast advancements, with the assistance of IoT, a great percentage of heterogeneou...
The data that medical sensors collect can be overwhelming, making it challenging to glean the most r...
Machine learning systems (MLSys) are emerging in the Internet of Things (IoT) to provision edge inte...
INST: L_042Edge computing is an essential technology to enable machine learning capabilities on IoT ...
Machine learning is one of the emerging technologies that has grabbed the attention of academicians ...