Munich/Miami, Germany/USA – 18 November 2019 – Infineon Technologies AG (FSE: IFX / OTCQX: IFNNY) and Klika Tech have formed a partnership to develop innovative solutions for smart buildings based on Infineon’s semiconductor portfolio and Klika Tech integrations of IoT Cloud and Amazon Web Services (AWS).
“Klika Tech is a strong addition to Infineon’s partner network, offering complementary capabilities to develop innovative solutions for smart building applications,” said Oliver Henning, Head of Partnership Management & Emerging Application Business at Infineon’s Power Management & Multimarket division. “
Klika Tech is a global developer of end-to-end IoT and Cloud solutions and an Amazon Partner Network (APN) Advanced Consulting Partner. The company is supporting product development based on Infineon’s solutions and provides deep, multi-domain and multi-industry experience for the collaborative launch of systems, products and market-ready solutions, as well as rapid development kits with full AWS cloud integrations. The companies are focusing on end-to-end solutions across applications such as smart building, smart city, smart home, connected devices as well as autonomous and electrified mobility.
“Collaborations among hardware, software and services providers are the genesis of the custom IoT and Cloud solutions that are enabling companies to reduce their development efforts and expedite time to market. This holds especially true for smart building and smart home applications.” said Gennadiy M. Borisov, President and Co-CEO at Klika Tech, Inc. “We look forward to building on our relationship with Infineon and the integration of their outstanding sensor portfolio with AWS services.”
Heating, Ventilation, and Air Conditioning (HVAC) system performance is a critical part of business operations. Maintaining clean, safe environments is a particularly acute concern for airports, hospitals, and similar critical infrastructures. Unscheduled downtime of HVAC systems can cause unplanned costs for customers, impact employee productivity, lead to IT downtime, and lead to health problems for occupants.
Scheduled maintenance of a business HVAC service program will not always identify problems that can lead to machine failure or ineffective operation. Solutions based on Cloud and Machine Learning (ML) provide predictive maintenance capabilities for current equipment condition analysis, informs maintenance personnel, and can trigger specific tasks to keep machines running at optimum levels. Implementing a predictive maintenance plan can detect improper installation, make equipment more energy efficient, predict costly failures, and extend equipment life to reduce total costs of ownership.
