Common Use Cases
Companies can now collect information for a number of smart sensor, wearable, and consumer electronic sources, leveraging the right data to develop intuitive features and apply analytics that generate effective insights for business goals. With the rise in IoT, more processes will be automated using machine-to-device communication, powered by algorithms developed using Artificial Intelligence (AI) and deep learning. Competitive advantage will be gained in the use of data streams to improve efficiency, security, operations, inventory, and allow for new revenue opportunities.
SFL Scientific allows companies to analyze the high volume sensor data, employing time-series machine learning techniques in real-time. We have the tools, experience, and partnerships necessary to truly work with your big data volumes at scale, and not just in a local environment.
Safety & Maintenance: Analyze the continuous stream of real-time data at any point in a system's operation (e.g., behavior, environment, mechanical performance, etc.). Our data scientists build algorithms to predict problems, determine best operational practices, and enhance production.
Automation: Automate routine tasks, events, and triggers, removing the need for costly and error-prone manual entry, transcription, sentiment surveys, and similar processes. Create custom solutions that allow your workforce to focus on creative tasks, strategy, and bigger business challenges.
Smart Sensors: Apply IoT infrastructure and predictive algorithms to track key events and information in your business.
Smart Meters: Use readouts to gain high-resolution and up to the minute insights into energy consumption patterns across structures and customer types, while gaining real-time insights into grid operations for forecasting.
Intel® IoT: From modular components to market-ready systems, Intel provides scalable, interoperable solutions that accelerate deployment of intelligent devices, cloud connectivity, and end-to-end analytics.
Time-series and machine learning methods can be applied to wearables and other interactive electronics to characterize events, movement, and learn a user's behavior.
Fitness: Monitor and predict activity from a variety of sensors and available sources. Whether a new spin on exercise tracking or integrated solutions with voice control, we provide full support and development.
Health: Track vital signs and predict acute health events from common biological signals such as ECG and EEG, or from singular and behavioral events such as falls and breathing patterns. Our work includes algorithms for heart pumps, offloading devices, and safety equipment.
With increased competition in the home automation space, mass adoption of smart systems and products remains centered around execution and implementation. Let's work together to find the best solution for your product and build a robust technological backbone.
Communication: We develop algorithms for standard and private protocols, providing engineering, time-series analysis, and audio analytics. We develop private integrations and voice activation for popular apps and auxiliary devices such as Amazon Alexa.
Smart Home: We create algorithms for signal monitoring, prescriptive maintenance, and alert systems for home security HVAC, solar, and other device classes.
Leverage sensor data to enable smarter supply chain management decisions and to achieve operational efficiency across fleets, warehouse, and employees. We build end to end solutions, incorporating connectivity, cloud services, security, and hardware needs with predictive analytics.
Asset Tracking: Garner granular insight with cloud and predictive analytics to inform and allow real-time monitoring of condition and delivery information.
Fleet Management: Optimize operations by modeling real-time conditions, incorporating traffic, weather, and other information sources. Plot more efficient routes and activity for every situation. Predict and mitigate disruptions and risks to deliver more value to your business.
Imaging: With cameras as sensors, AI and deep learning technologies play a key role in a number of emerging areas in shipping, cargo, and distribution. We use the latest NVIDIA GPU accelerated solutions to deploy deep learning algorithms to a range of emerging technologies including drones, robotics, screeners, surveillance, and camera systems.
Cargo & Inventory: Connect smart labels and sensors to monitor cargo integrity and control storage conditions. We build systems with end-to-end visibility into the delivery process.