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IoT use cases: AI/Machine Learning

AI and Machine Learning in IoT

By gathering data, analyzing trends, detecting anomalies, and learning what actions or conditions are most suitable, machine learning in IoT systems can help users automate and make the best choices while saving resources from manual work. First, users identify a goal for the system to reach and develop algorithms to predict data patterns. The system’s predictions are then qualified by the user, approving it as a basis for decisions within the business’ operations.

Applications for AI/ML in IoT are many and broad. For example, the technology is deployed within agriculture, weather prediction models, and driverless transport systems, to name a few areas. In addition, users lay the foundation for the future of true AI in IoT through the systems working with machine learning today.

7 hits

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Smart Agriculture

Agriculture and AI in the service of climate

Extensive field, soil, satellite and sensor data will be used as input to model algorithms driven by AI/ML and spatial analysis (GIS). These algorithms will be used to create prescription files to control inputs and other actions in the fields as efficiently and climate friendly as possible.

Type: AI/Machine Learning
Application: R&D projects

ELLOSS – Energy efficient buildings using multiple energy sources and smart control with AI

Sensative, together with Örebroporten, wants to explore and verify how much we can reduce a property's CO2 emissions and energy consumption with the help of our IoT platform, AI and a relatively low investment in 48 volts micro-grid networks with solar cells, batteries and 48 V lighting, heating systems, and more.

Type: AI/Machine Learning, IoT integration
Application: PropTech, R&D projects, Sensative customer case

DAIS – Distributed Artificial Intelligent Systems

DAIS approach is to develop intelligent, secure and trustworthy systems for industrial applications to provide comprehensive cost and energy-efficient solutions of intelligent, end-to-end secure, trustworthy connectivity and interoperability to bring the Internet of Things and Artificial Intelligence together.

Type: AI/Machine Learning, IoT integration
Application: R&D projects, Security

Smart Building

Artificial Intelligence for Real Estate

In the project we will choose the appropriate AI/ML framework and integrate it into Yggio together with the extension of the public API

Type: AI/Machine Learning
Application: PropTech, R&D projects, Security

Smart Agriculture

Automatic validation of sensor data

The project will, with the help opf Machine Learning and AI algorithms, identify common sensor problems for the most interesting sensors in agriculture, including sensors for temperature, humidity, precipitation and wind in weather stations, sensors for soil temperature and humidity, etc.

Type: AI/Machine Learning, Air humidity, Ground moisture, IoT integration, LoRaWAN, Open/Close, Temperature
Application: Analytics, Predictive maintenance, R&D projects, Sensative customer case

CritiSec – Critical Infrastructure Security

An important part of the digitalization process is to connect critical infrastructures to the Internet. This creates a wide range of opportunities for security attacks with a huge potential impact, and thus makes our society vulnerable and unsafe.

Type: AI/Machine Learning, IoT integration
Application: R&D projects, Security, Sensative customer case

Convince

CONVINcE addresses the challenge of reducing the power consumption in IP-based video networks with an end-to-end approach, from the headend where contents are encoded and streamed to the terminals where they are consumed, embracing the Content Delivery Networks (CDN) and the core and access networks.

Type: AI/Machine Learning, IoT integration
Application: R&D projects

IoT use cases: AI/Machine Learning

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