Smart connected devices and Internet of Things (IoT) are emerging technologies that are impacting diverse industries, including automotive, energy, healthcare, retail, smart manufacturing, smart buildings and homes, smart transportation, etc. Combining internet-connected devices with cloud computing, machine learning, and other data analytics approaches is enabling products and solutions that are transforming the way we live and work. For example, Smart Medical Devices are key components of new products and solutions that may help healthcare professionals to improve health outcomes from anywhere, leading to increased value for the patient.

However, a system developer working on such products and services faces challenges in capturing, storing, and analyzing the Big Data generated from a multitude of devices. Also, integrating Smart Devices, IoT and Big Data raises specific challenges for data acquisition, reduction, and transmission, using increasingly sophisticated technologies such as RFID tags, Wireless Sensor Nodes and mobile devices.

Using the development of a Smart Medical Device based healthcare application as an example, this presentation will discuss how engineers and scientists creating smart devices and IoT systems can use MATLAB and Simulink to access and analyze huge data sets from devices, sensors, and databases; apply deep learning and other machine-learning techniques to develop predictive models; and design and test smart devices that wirelessly interact with cloud services like ThingSpeak™, an analytic IoT platform that can run MATLAB code on demand in the cloud.