Long range LiDAR characterisation for obstacle detection for use by the visually impaired and blind

Obstacle detection and avoidance is a huge area of interest for autonomous vehicles and, as such, has become an important research topic. Detecting and identifying obstacles enables navigation through an ever changing environment. This work looks at the technology used in self-driving vehicles and examines whether the same technology could be used to aid in navigation for visually impaired and blind (VIB) people. For autonomous vehicles, obstacle detection relies on different sensor modalities to provide information on the vehicles surroundings. A combination of the same sensors placed on a white cane could be used to perform free-space assessment over the whole height of the user and provide additional environmental information not available from the cane alone. This provides its own challenges and advantages. The speeds are much slower when dealing with pedestrians and scanning can be achieved by the movement of the cane. However, the weight and size must be significantly reduced. The full system will be integrated into a smart cane and will consist of four main sensors as well as range sensors. The aim of this work is to report on the characterisation of a long range LiDAR (up to 10m) that will be integrated into a smart white cane developed as part of the INSPEX H2020 project

Shock-induced aluminum nitride based MEMS energy harvester to power a leadless pacemaker

The next generation of implantable leadless pacemakers will require vibrational energy harvesters in order to increase the lifetime of the pacemaker. This paper reports for the first time the use of a piezoelectric MEMS linear energy harvester device that fits inside a pacemaker capsule. The silicon based MEMS cantilever device uses CMOS compatible Aluminum Nitride as the piezoelectric layer. The developed harvester operates based on a shock-induced vibration that is generated from the low frequency (60–240 beats per minute) high acceleration (>1 g) vibration of the heart. The off-resonance, high g impulses force the high-frequency harvester to oscillate at its resonant frequency. A power density of 97 and 454 μW cm−3 g−2 was achieved for a heart rate of 60 and 240 beats per minute respectively. The forced oscillation causes the linear harvester to dampen after 100–200 ms which reduces the average power compared to a typical sinusoidal excitation. A two and four cantilever system occupies 35% and 70% of the overall volume of the capsule while obtaining 2.98 and 5.96 μW respectively at a heart rate of 60 bpm respectively and 1 g acceleration. The results in this paper demonstrate that a shock-induced linear MEMS harvester can produce enough electrical energy from the vibration of a heart to power a leadless pacemaker while maintaining a small volume

SmartVista: Smart Autonomous Multi Modal Sensors for Vital Signs Monitoring

Cardiovascular diseases (CVD) remain the leading cause of mortality and a major cause of morbidity in Europe. Every year there are more than 6 million new cases of CVD in the EU and more than 11 million in Europe as a whole. With almost 49 million people living with the disease in the EU, the cost to the EU economies is 210 billion EUR a year. There is a growing demand for a reliable cardiac monitoring system to catch the intermittent abnormalities and detect critical cardiac behaviours which, in extreme cases, can lead to sudden death. The objective of the Smart Autonomous Multi Modal Sensors for Vital Signs Monitoring (SmartVista) project is to develop and demonstrate a next generation, cost-effective, smart multimodal sensing platform to reduce incidences of sudden death caused by CVD, and will contribute to the EU vision of an Internet of Things for healthcare. The key innovation in SmartVista is to integrate 1D/2D nanomaterials based sensors to monitor the heart, thermoelectric energy harvesters to extract energy from the body to power the system and printable battery systems to store this energy. Together these will result in a self-powered device that will autonomously monitor the electrocardiograph, respiratory flow, oxygen flow and temperature of the patient. This information will then be transmitted wirelessly for online health processing. This real-time self-powered monitoring of a patient's health is currently not available. Thus, the technology that will be developed in SmartVista will position us at the forefront of digital health and wearable biosensor technology for wireless monitoring in hospitals and of remote patients, both of which are necessary in this era of an aging population

INSPEX: design and integration of a portable/wearable smart spatial exploration system

The INSPEX H2020 project main objective is to integrate automotive-equivalent spatial exploration and obstacle detection functionalities into a portable/wearable multi-sensor, miniaturised, low power device. The INSPEX system will detect and localise in real-time static and mobile obstacles under various environmental conditions in 3D. Potential applications range from safer human navigation in reduced visibility, small robot/drone obstacle avoidance systems to navigation for the visually/mobility impaired, this latter being the primary use-case considered in the project

SARMENTI: Smart multisensor embedded and secure system for soil nutrient and gaseous emission monitoring

Demand for sustainably produced food is driving current strategies for intensification of the agricultural sector worldwide. To meet these challenges farmers will need to adopt a whole-farm approach to resource efficiency. They will increase their productivity with a better application of knowledge per hectare. Optimising soil fertility will enable farmers to maximise their productivity and profitability with higher grass and crop yield and quality

Energy autonomous wearable sensors for smart healthcare: a review

Energy Autonomous Wearable Sensors (EAWS) have attracted a large interest due to their potential to provide reliable measurements and continuous bioelectric signals, which help to reduce health risk factors early on, ongoing assessment for disease prevention, and maintaining optimum, lifelong health quality. This review paper presents recent developments and state-of-the-art research related to three critical elements that enable an EAWS. The first element is wearable sensors, which monitor human body physiological signals and activities. Emphasis is given on explaining different types of transduction mechanisms presented, and emerging materials and fabrication techniques. The second element is the flexible and wearable energy storage device to drive low-power electronics and the software needed for automatic detection of unstable physiological parameters. The third is the flexible and stretchable energy harvesting module to recharge batteries for continuous operation of wearable sensors. We conclude by discussing some of the technical challenges in realizing energy-autonomous wearable sensing technologies and possible solutions for overcoming them

INSPEX: Make environment perception available as a portable system

Obstacle avoidance systems for autonomous vehicles combine multiple sensing technologies (i.e. LiDAR, Radar, Ultrasound and Visual) to detect different types of obstacles across the full range of lighting and weather conditions. Sensor data are fused with vehicle orientation (obtained for instance from an Inertial Measurement Unit and/or compass) and navigation subsystems. Power hungry, they require powerful computational capability, which limits their use to high-end vehicles and robots

Long range LiDAR characterisation for obstacle detection for use by the visually impaired and blind

Obstacle detection and avoidance is a huge area of interest for autonomous vehicles and, as such, has become an important research topic. Detecting and identifying obstacles enables navigation through an ever changing environment. This work looks at the technology used in self-driving vehicles and examines whether the same technology could be used to aid in navigation for visually impaired and blind (VIB) people. For autonomous vehicles, obstacle detection relies on different sensor modalities to provide information on the vehicles surroundings. A combination of the same sensors placed on a white cane could be used to perform free-space assessment over the whole height of the user and provide additional environmental information not available from the cane alone. This provides its own challenges and advantages. The speeds are much slower when dealing with pedestrians and scanning can be achieved by the movement of the cane. However, the weight and size must be significantly reduced. The full system will be integrated into a smart cane and will consist of four main sensors as well as range sensors. The aim of this work is to report on the characterisation of a long range LiDAR (up to 10m) that will be integrated into a smart white cane developed as part of the INSPEX H2020 project

SmartVista: Smart Autonomous Multi Modal Sensors for Vital Signs Monitoring

International audienceCardiovascular diseases (CVD) remain the leading cause of mortality and a major cause of morbidity in Europe. Every year there are more than 6 million new cases of CVD in the EU and more than 11 million in Europe as a whole. With almost 49 million people living with the disease in the EU, the cost to the EU economies is €210 billion a year. There is a growing demand for a reliable cardiac monitoring system to catch the intermittent abnormalities and detect critical cardiac behaviours which, in extreme cases, can lead to sudden death. The objective of the Smart Autonomous Multi Modal Sensors for Vital Signs Monitoring (SmartVista) project is to develop and demonstrate a next generation, cost-effective, smart multimodal sensing platform to reduce incidences of sudden death caused by CVD. The key innovation in SmartVista is to integrate 1D/2D nanomaterials based sensors to monitor the heart, thermoelectric energy harvesters to extract energy from the body to power the system and printable battery systems to store this energy. Together these will result in a self-powered device that will autonomously monitor the electrocardiograph, respiratory flow, oxygen flow and temperature of the patient. This information will then be transmitted wirelessly for online health processing. This real-time self-powered monitoring of a patient’s health in this manner is not currently available so the technology that will be developed in SmartVista will position us at the forefront of digital health and wearable biosensor technology for wireless monitoring in hospitals and of remote patients, both of which are necessary in this era of an aging population. The SmartVista platform enables wireless, real-time, continuous patient monitoring and delivers a seamless feed of patient data and will contribute to the EU vision of an Internet of Things for healthcare