The Internet of Things (IoT) market is in a constant state of positive evolution. It has undergone 3 phases since its inception nearly a decade ago. The first phase – the ‘connectivity’ phase was about connecting previously unconnected devices and assets to the cloud and heralded hardware innovation with the creation of new chips, modules to support wi-fi, BLE, cellular and other standards. The second phase was about device management and apps, the ability to perform command & control of the connected device using a mobile app. The second phase ushered improvements in capabilities such as over-the-air updates, mobile app experiences, and capture & storage of device data.
We’re now officially in the 3rd phase of the IoT. It’s all about the data. It encompasses the transmission, ingestion, pipeline management, storage, analysis, and extraction of information. This is the final frontier of IoT because the information can be harnessed in a variety of value-added ways to have a high impact on the business. Manufacturing companies, service organizations, public sector entities, Telcos, and other service providers are utilizing the data to improve operational efficiency, unlock new revenue streams, enhance customer experiences and manage risk.
Data analysis can produce descriptive, predictive, and prescriptive insights. The descriptive kind aggregates the data and ‘slices & dices’ it along different dimensions. This is basic reporting or business intelligence as it's sometimes called. The next level of analysis is trying to predict outcomes. This is challenging because it goes beyond reporting into quantitative modeling that uses a combination of variables to identify data patterns. Artificial Intelligence (AI), specifically its subset of machine learning (ML), has a major role to play in this area using either regression analysis, Bayesian inference, neural network, and a variety of other methods. It’s a bigger challenge in IoT where the volume, variety, and velocity of the data from a fleet of connected devices can be immense. But herein lies the transformational opportunity for business – the organizations that leverage the ambient IoT data from their assets are best positioned to gain competitive advantage and win.
Ayla is Uniquely Positioned for AI Success
Ayla IoT aims to be the creator of the ‘easy button’ for AI in IoT. That means creating the best-in-class processes for data ingestion, processing, and transformation combined with leading-edge data science turnkey models that are industry-specific, quick to deploy, and effective. These models are currently in use in internet service providers to improve network performance and customer operations, and in foodservice enterprises to prevent asset downtime and reduce risk, and in consumer brands to improve product quality. The information is delivered through application functionality whether dashboard charts, alerts & notifications or automated workflows.
There is a notion that any specialist analytics company, with enough investment, can build AI models for IoT. We emphatically disagree – developing effective models for IoT is dependent on a deep understanding of device data, and Ayla’s strong foundations in edge-level details including module, firmware, and protocols uniquely position us to extract meaningful value from the data. Additionally, Ayla’s vast experience of launching connected devices ranging from smart home devices and appliances, enterprise equipment, and service provider customer premise equipment (CPE) is a competitive moat when it comes to leveraging AI in IoT.
Ayla’s bold vision for the future is to have hundreds of Machine Learning models – by market, by product line, by solution area – available as a broad library for customers to choose from, benefiting roles as diverse as product engineering, product management, R&D, Innovation, and Marketing.
To learn more about how Ayla is leading the AI revolution in IoT contact us and schedule a consultation.