IoT-based systems for soil nutrients assessment in horticulture

Soil nutrients assessment has great importance in horticulture. Implementation of an information system for horticulture faces many challenges: (i) great spatial variability within farms (e.g., hilly topography); (ii) different soil properties (e.g., different water holding capacity, different content in sand, sit, clay, and soil organic matter, different pH, and different permeability) for different cultivated plants; (iii) different soil nutrient uptake by different cultivated plants; (iv) small size of monoculture; and (v) great variety of farm components, agroecological zone, and socio-economic factors. Advances in information and communication technologies enable creation of low cost, efficient information systems that would improve resources management and increase productivity and sustainability of horticultural farms. We present an information system based on different sensing capability, Internet of Things, and mobile application for horticultural farms. An overview on different techniques and technologies for soil fertility evaluation is also presented. The results obtained in a botanical garden that simulates the diversity of environment and plant diversity of a horticultural farm are discussed considering the challenges identified in the literature and field research. The study provides a theoretical basis and technical support for the development of technologies that enable horticultural farmers to improve resources management.info:eu-repo/semantics/publishedVersio

Development of dry textile electrodes for electromiography: a comparison between knitted structures and conductive yarns

The paper presents a practical approach concerning the design, implementation and testing of dry textile electrodes for surface electromyography purposes. Several knitted structures were designed and knitted with conductive yarns, in order to compare the influence of the fabric structure in the electrode performance. The effect of the type of conductive yarn was also studied by comparing three different yarns. It was found that the textile electrodes perform well for sEMG acquisition, with a clear depiction of the muscle activity produced. There are significant differences between the structures tested and there is also some influence from the yarn used.This work is supported by Portuguese National Funding, through FCT - Fundação para a Ciência e a Tecnologia, in the framework of project EHRPhysio PTDC/DTP-DES/1661/2012 and project UID/CTM/00264/2013

Treat me well : affective and physiological feedback for wheelchair users

This work reports a electrocardiograph and skin conductivity hardware architecture, based on E-textile electrodes, attached to a wheelchair for affective and physiological computing. Appropriate conditioning circuits and a microcontroller platform that performs acquisition, primary processing, and communication using Bluetooth were designed and implemented. To increase the accuracy and repeatability of the skin conductivity measuring channel, force measurement sensors were attached to the system certifying measuring contact force on the electrode level. Advanced processing including Rwave peak detector, adaptive filtering and autonomic nervous system analysis based on wavelets transform was designed and implemented on a server. A central design of affective recognition and biofeedback system is described.Fundação para a Ciência e a Tecnologia (FCT

Multi-sensing node architecture for water quality monitoring

Peer Reviewe

Fear or humour in anti-smoking campaigns? Impact on perceived effectiveness and support for tobacco control policies

Several anti-smoking campaigns have been used for decades to reduce smoking consumption. However, so far, there is no consensus regarding the effectiveness of inducing distinct emotions in reducing smoke consumption. This study tested the effects of two types of anti-smoking ads, inducing fear or humor, on emotions, perceived effectiveness, support for tobacco control policies, urges to smoke, and susceptibility to smoke. Participants (N = 108; 54 smokers) of both genders were randomly assigned to one of the two following emotion ads condition: fear (N = 52) or humor (N = 56). During exposure, the continuous flow of their emotions by self-report and physiologically was collected. Measures of ads impact on emotions, perceived effectiveness, urges and susceptibility to smoking, and support for tobacco policies were applied after exposure. The results have shown that fear ads were perceived as more effective and reduced the urges to smoke in smokers. Non-smokers were more supportive of tobacco control policies. In conclusion, this study showed that fear campaigns can reduce the urge to smoke among smokers and are perceived to be more effective. This perceived effectiveness can be partially explained by feelings of fear, regardless the other emotions it also triggers, and of the smoking status.info:eu-repo/semantics/publishedVersio

Neural architecture search for 1D CNNs - Different approaches tests and measurements

In the field of sensors, in areas such as industrial, clinical, or environment, it is common to find one dimensional (1D) formatted data (e.g., electrocardiogram, temperature, power consumption). A very promising technique for modelling this information is the use of One Dimensional Convolutional Neural Networks (1D CNN), which introduces a new challenge, namely how to define the best architecture for a 1D CNN. This manuscript addresses the concept of One Dimensional Neural Architecture Search (1D NAS), an approach that automates the search for the best combination of Neuronal Networks hyperparameters (model architecture), including both structural and training hyperparameters, for optimising 1D CNNs. This work includes the implementation of search processes for 1D CNN architectures based on five strategies: greedy, random, Bayesian, hyperband, and genetic approaches to perform, collect, and analyse the results obtained by each strategy scenario. For the analysis, we conducted 125 experiments, followed by a thorough evaluation from multiple perspectives, including the best-performing model in terms of accuracy, consistency, variability, total running time, and computational resource consumption. Finally, by presenting the optimised 1D CNN architecture, the results for the manuscript’s research question (a real-life clinical case) were provided.info:eu-repo/semantics/publishedVersio

Serious game for physical rehabilitation: measuring the effectiveness of virtual and real training environments

Recent advances in low-cost natural user interfaces such as Microsoft Kinect and Leap Motion controller allow the Virtual Reality implementation of 3D serious games for, posture, upper limb and lower limb rehabilitation purposes. However, it is very important to compare the results obtained by the users that train in virtual and real environments. This paper presents a virtual reality serious game for upper limb rehabilitation using a natural user interface expressed by Leap Motion controller. One of the developed virtual reality serious game for rehabilitation is converted to a real scenario with the same elements and rules and the same aims of physical rehabilitation. In order to extract appropriate information from the serious game based on real objects a RFID technology was used together with software components developed in LabVIEW. The evaluation of hand muscles' activity during the training session is based on the usage of thermography that permits to measure in an unobtrusive way the distribution of the temperature on the hands' level. Based on analysis of thermographic images obtained before and after serious game practice, the level of activity of specific muscles associated with training for virtual and real scenario is extracted. Experimental results that are also included in the paper underline the effectiveness of the proposed method for the comparison of the training in virtual and real scenarios.info:eu-repo/semantics/acceptedVersio

Study of latencies in ThingSpeak

IoT platforms play an important role on modern measurement systems because they allow the ingestion and processing of huge amounts of data (big data). Given the increasing use of these platforms, it is important to characterize their performance and robustness in real application scenarios. The paper analyzes the ThingSpeak platform by measuring the latencies associated to data packets sent to cloud and replied back, and by checking the consistency of the returned data. Several experiments were done considering different ways to access the platform: REST API, MQTT API, and MQTT broker alone. For each experiment, the methodology is explained, results are presented, and conclusions are extracted. The REST and MQTT APIs have similar performances, with roundtrip times between 1 s and 3 s. The MQTT broker alone is more agile, with roundtrip times below 250 ms. In all cases, the up and down links are far from being symmetric, with the uplink delay showing higher variance than the downlink delay. The obtained results can serve as a reference for other IoT platforms and provide guidelines for application development.info:eu-repo/semantics/publishedVersio