Per Lynggaard received his M.Sc. in EE and IT and his Ph.D. in the areas of artificial intelligence and Internet of Things from Aalborg University. Dr. Lynggaard has been employed at Aalborg University as an Associate Professor (8 years) with the following research and teaching areas: Internet of Things, machine learning, digital signal processing, and wireless communication. Today he is employed at the Technical University of Denmark as a Professor in Internet of Things.
Beyond the academic achievement Dr. Lynggaard has a long track record from a professional industrial career (23 years) with focus on technical-scientific research, development, and implementation with focus on creativity and innovation. He has received several honours and rewards during this period, and he has been headhunted several times.
Per Lynggaard is an expert in the Internet of Things (IoT) area including subareas such as:
- Machine learning
- Big-data in relation to IoT
- Digital signal processing
- Wireless Sensor Networks (WSN) technologies
- Communication and security in WSN
- Advanced analog and digital electronics
- Programming embedded platforms
- Object-oriented software construction and modelling
- High-level client / server communication and programming
- Integrated circuit design
He has been involved in numerous research projects funded by the European Commission, etc.
Conference Papers:
A Smart Home Development Tool combining Simulation, Emulation and Real-World IoT
Lynggaard P., 2011, Conference: AAU / CMI, Internet of Things – Our Environment Becomes Intelligent.
Smart Home Wireless Sensor Nodes, Addressing the Challenges using Smart Objects and Artificial Intelligence
Lynggaard P., 2013, WWRF Conference: Wireless Enabled Smart Societies in the 2020s.
A simulation model for aligning smart home networks and deploying smart objects
Lynggaard P., 2013, the 6th international CMI conference, Copenhagen, Denmark.
Smart Cities and the Ageing Population
Skouby K.E., Kivimäki A., Haukiputo L., Lynggaard P., Windekilde I., 2014, the 32nd Meeting of WWRF, Marrakech, Marokko.
How IoT, AAI can contribute to smart homes / cities services, The role of innovation
Skouby K.E., Lynggaard, Windekilde I., 2014, Challenges for European policy and business conference, 2014, Brussels, Belgium.
A User-friendly Interface using Image Processing in Mobile Phones
Lynggaard P., Skouby K.E., 2014, the 32nd Meeting of WWRF, Marrakech, Marokko.
Challenges and visons for future smart cities and digizens
Skouby K.E., Ahokangas P. , Kivimäri A., Haukipuro L., Lynggaard P., Windekild I., 2013, WWRF Conference: Wireless Enabled Smart Societies in the 2020s.
A smart home and smart city infrastructure that encourage citizen’s involvement
Skouby K.E., Kivimäri A., Haukipuro L., Lynggaard P., Windekild I., 2014, 33rd Meeting of WWRF, in Guildford, UK.
A fall-detection system that uses body area network and thermal energy harvesting technology
Lynggaard P., 2018, 11th CMI International Conference.
Journal Papers:
Distributed Smart Home Activity Recommender System Using Hidden Markov Model Principles
Lynggaard P., 2012, Scientific Journal of the University of Szczecin no. 762 TOM I p359-369.
A Distributed Smart Home Artificial Intelligence System
Lynggaard P., 2012, Scientific Journal of the University of Szczecin no. 763 TOM II p521-531.
Smart home and smart city solutions enabled by 5G, IoT, AAI and CoT Services
Skouby K.E., Lynggaard P., 2014, IEEE EPTC.
Deploying 5G-technologies in smart city and smart home wireless sensor networks with interferences
Lynggaard P., Skouby K.E., 2015, Wireless Personal Communications, Springer.
The Potential of Wastewater Energy Recovery in Smart Buildings by using Internet of Things Technology
Lynggaard P., 2015, WWRF Meeting 35.
An Energy Efficient Adaptive Wireless Link for Farms based on IoT technologies
Blaszcyk T., Lynggaard P., 2016, WirelessVITAE 2015, IEEE.
An Energy-Efficient Link with Adaptive Transmit Power Control for Long Range Networks
Lynggaard P., Blaszcyk T., 2016, IEEE.
Complex IoT Systems as Enablers for Smart Homes in a Smart City Vision
Lynggaard P., Skouby K.E., 2016, Sensors.
Improving Internet coverage in rural Africa by using passive repeaters in the home
Lynggaard P.,2016, Nordic and Baltic journal of ICTs.
Improve Google Loon’s Indoor LTE Coverage in Rural Africa by Using Passive Repeaters
Lynggaard P., 2017, Nordic and Baltic Journal of Information and Communications Technologies, Bind 2017, Nr. 1, 6, 2017, s. 91-106.
A self-supporting wireless IoT node that uses kinetic energy harvesting
Lynggaard P., 2017, Internet of Things Business Models, Users, and Networks. IEEE.
Using machine learning for adaptive interference suppression in wireless sensor networks
Lynggaard P., 2018, IEEE Sensor Journal Bind 18, Nr. 21, 8445591, 01.11.2018, s. 8820-8826.
Towards airflow sensors with energy harvesting and wireless transmitting properties
Blaszcyk T., Sørensen J., Lynggaard P., Larsen K., 2018, Advanced Materials Letter (ACL), Bind 9, Nr. 5, 05.2018, s. 311-319.
Detecting Premature Ventricular Contraction by using Regulated Discriminant Analysis with very sparse training data
Lynggaard P., 2019, Applied Artificial Intelligence.
Controlling Interferences in Smart Building IoT Networks using Machine Learning
Lynggaard P., 2019, International Journal of Sensor Networks.
A self-powered body area network node that uses thermal energy harvesting
Lynggaard P., 2019, Nordic and Baltic Journal of Information and Communications Technologies.
Using neural networks to reduce sensor cluster interferences and power consumption in smart cities
Lynggaard P., 2020, International Journal of Sensor Networks, Vol/bind: 32
Ph.d. dissertation:
Artificial intelligence and Internet of Things in a “smart home” context: A Distributed System Architecture.
Lynggaard P., 2013, 1.udg. Department of Electronic Systems, Aalborg University.