SENSORNETS 2022 Abstracts

Area 1 - Intelligent Data Analysis and Processing for Sensor Networks
Full Papers Short Papers
Area 2 - Sensor Networks and Architectures
Full Papers Short Papers
Area 3 - Sensor Networks Applications
Full Papers Short Papers

Area 1 - Intelligent Data Analysis and Processing for Sensor Networks

Full Papers
Paper Nr: 18
Title:

Towards a Floating Plastic Waste Early Warning System
Authors:

Gábor Paller and Gábor Élő
Abstract: Plastic waste in living waters is a worldwide problem. One particular variant of this problem is floating plastic waste, e.g. plastic bottles or bags. Rivers often carry large amount of floating plastic waste, due to unauthorized or not properly maintained waste dumps installed in the rivers’ flood plain. It is of utmost importance that environmental protection agencies be aware of such large-scale plastic pollutions so that they can initiate appropriate countermeasures. This paper presents two iterations of an early warning system designed to alert environmental protection agencies of plastic waste pollution. These systems are based on processing camera images but while the first iteration uses motion detection for identifying relevant images, the second iteration adopted a machine learning algorithm deployed in edge computing architecture. Better selectivity of the machine learning-based solution significantly eases the burden on the operators of the early warning system.
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Short Papers
Paper Nr: 2
Title:

Comparison of Two Different Radar Concepts for Pedestrian Protection on Bus Stops
Authors:

E. Streck, R. Herschel, P. Wallrath, M. Sunderam and G. Elger
Abstract: This paper presents the joint work from the “HORIS” project, with a focus on pedestrian detection at bus-stops by radar sensors mounted in the infrastructure to support future autonomous driving and protecting pedestrians in critical situations. Two sensor systems are investigated and evaluated. The first based on single radar sensor phase-sensitive raw data analysis and the second based on sensor data fusion of cluster data with two radar sensors using neural networks to predict the position of pedestrians.
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Paper Nr: 3
Title:

Surface Light Barriers
Authors:

Theo Gabloffsky, Britta Kruse and Ralf Salomon
Abstract: It should be known to almost all readers that light barriers are commonly used for measuring the speed of various objects. These devices are easy to use, quite robust, and of low cost. Despite their advantages, light barriers exhibit certain limitations that occur when the objects of interest move in more than one spatial dimension. This paper discusses a physical setup in which light barriers can also be used in case of two-dimensional trajectories. However, this setup requires rather complicated calculations. Therefore, this paper performs these calculations by means of different neural network models. The results show that backpropagation networks as well as radial basis functions are able to achieve a residual error less than 0.21 %, which is more than sufficient for most sports and everyday applications.
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Paper Nr: 16
Title:

A Distributed Intelligent Intrusion Detection System based on Parallel Machine Learning and Big Data Analysis
Authors:

Faten Louati, Farah Barika Ktata and Ikram Amous Ben Amor
Abstract: Networking security continue to be a serious challenge for all domains because of the increasing number of attacks launched every day due to the advent of connected devices and the emergence of the Internet. Hence, Intrusion detection system comes into focus, especially with the inception of big data challenges. In this paper, we propose a distributed and parallel intrusion detection system suitable for big data environments using machine learning-based multi agent system and big data analysis.
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Paper Nr: 22
Title:

Semantic Segmentation of Retinal Blood Vessels from Fundus Images by using CNN and the Random Forest Algorithm
Authors:

Ayoub Skouta, Abdelali Elmoufidi, Said Jai-Andaloussi and Ouail Ouchetto
Abstract: Abstract: In this paper, we present a new study to improve the automated segmentation of blood vessels in diabetic retinopathy images. Pre-processing is necessary due to the contrast between the blood vessels and the background, as well as the uneven illumination of the retinal images, in order to produce better quality data to be used in further processing. We use data augmentation techniques to increase the amount of accessible data in the dataset to overcome the data sparsity problem that deep learning requires. We then use the CNN VGG16 architecture to extract the feature from the preprocessed background images. The Random Forest method will then use the extracted attributes as input parameters. We used part of the augmented dataset to train the model (1764 images, representing the training set); the rest of the dataset will be used to test the model (196 images, representing the test set). Regarding the model validation phase, we used the dedicated part for testing the DRIVE dataset. Promising results compared to the state of the art were obtained. The method achieved an accuracy of 98.7%, a sensitivity of 97.4% and specificity of 99.5%. A comparison with some recent previous work in the literature has shown a significant advancement in our proposal.
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Paper Nr: 27
Title:

Integration of FIWARE and IoT based Named Data Networking (IoT-NDN)
Authors:

Mohamed Ahmed Hail, Ian Pösse and Stefan Fischer
Abstract: IoT systems have taken on an essential role in our life. IoT devices are strongly integrated into several sectors such as Smart Healthcare, Smart Cities, Smart Energy, Smart Industry, etc. and deliver important data. Designing, building, and implementing IoT systems are significant challenges because of IoT requirements such as mobility, energy consumption, and limited device memory. To mitigate such challenges, opportunities to test and evaluate IoT systems early in the first development phases are important to reduce cost and effort. Different systems have been proposed to aid such development, aiming at different key challenges. One of these systems is FIWARE, an open source IoT middleware, designed to ease data transportation and big data tasks. It has been established as an ecosystem technology used for optimizing the development of several applications and services in IoT. Key feature is the standardized architecture for gathering context information and managing these contexts in cloud based IoT and big data applications. In this paper, we discuss the integration of FIWARE software and IoT-NDN. IoT-NDN is an IoT system based on the Named Data Networking (NDN) communication paradigm. NDN is a communication protocol developed for the Internet and uses hierarchical names instead of IP addresses to deliver data on the Internet. IoT-NDN is an advanced architecture of NDN, conceding the requirements and limitations of IoT devices. In this paper we present an approach and architecture to integrate FIWARE and IoT-NDN. This integration eases implementation of IoT-NDN in existing applications, since a transparent compatibility between both systems can be achieved.
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Area 2 - Sensor Networks and Architectures

Full Papers
Paper Nr: 7
Title:

Improving Power and Energy Efficiency of Linearly Equalized Baseband Cable Transmission Links
Authors:

Christoph Lange and Andreas Ahrens
Abstract: Telecommunication networks have been identified to exhibit a substantial electrical power and energy demand. Therefore it is important to utilize power and energy efficient systems as building blocks for such networks. In wired access networks copper cables are used for highspeed data transmission. Important technical indicators for power and energy efficiency of transmission systems are transmit power and energy per bit. In this work it is investigated how transmit power and energy per bit in linearly equalized multilevel baseband cable transmission systems can be minimized by exploiting degrees of freedom in the transmission link design for given throughput and transmission quality. First, the constellation size is a degree of freedom: Its optimization leads to minimum values of transmit power and energy per bit depending on the interplay between throughput and band limitation of the cable. Second, the partitioning of the equalization to transmitter and receiver is a degree of freedom: Here, a uniform distribution of the linear equalizing function is found to be optimum in terms of minimum transmit power or energy per bit at a given transmission performance and quality. The results show that the optimization of constellation size and equalization partitioning leads to significant transmit power and energy-per-bit savings compared to conventional baseband cable transmission systems.
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Paper Nr: 11
Title:

Design of a Reconfigurable Multimodal Wearable Sensor Network (RMWSN) for Human Health and Ambience Monitoring
Authors:

Surendar Devasundaram, Andrea Raymond, Mark Aldritz Dela Virgen, Drue Shapiro and Joon-Hyuk Park
Abstract: The studies of human physiology, movement biomechanics and environmental interaction are generally conducted in laboratory settings using standard lab equipment such as Electrocardiography (ECG), respiration belt, motion capture cameras and a force-plate instrumented treadmill. With recent advancements in wearable technology, research on human behaviour, physiology and biomechanics in real-world environments has become much more viable and offers a means to collect real-world data from a broader range of activities. However, current wearable devices are typically a stand-alone system, each employing its own hardware and software interfaces that often vary between different systems, thus making it difficult to simultaneously integrate and instrument them on a user for synchronous multimodal measurements. To overcome this limitation, we propose a reconfigurable multimodal wearable sensor network (RMWSN) for real-time monitoring and data acquisition of various biomechanics, physiological and environmental parameters. The RMWSN incorporates a two-tier sensor network: the first tier utilizes wearable sensors with a microcontroller and the second tier consists of an efficient edge computing device for real-time data processing, data logging and wireless data transmission. The novel feature of the system that differentiates itself from existing wearable sensor systems is the modular and reconfigurable design in a wearable form, its scalability, easy accessibility, and integration with external computing devices. The outcomes of this research demonstrate an efficient multimodal wearable sensor network for use in many applications for human health and ambience monitoring.
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Paper Nr: 15
Title:

Storage Allocation for Camera Sensor Networks using Feedback-based Price Discrimination
Authors:

Alexandre Martins, Hung-Yu Wei and Karl-Erik Årzén
Abstract: Camera sensor networks, mainly with surveillance cameras, are growing in size and complexity. Storage space is the prime resource in such systems but current surveillance setups are still very much centralized and limited in resources due to cost and security constraints. Allocating the correct amount of storage to each camera sensor considering their large difference in characteristics and video content is challenging. In this paper we propose a framework using feedback-based price discrimination of storage resources in order to guarantee a uniform quality level of the videos in camera sensor networks, regardless of the specific camera sensor parameters. We designed a lightweight solution using simple video quality metrics, cascade control and PI (Proportional and Integral) controllers to define the optimal price of resources per camera.
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Paper Nr: 32
Title:

On Configuring Directional Transmission for Path Exposure Reliability in Energy Harvesting Wireless Sensor Networks
Authors:

Abdulsalam Basabaa and Ehab S. Elmallah
Abstract: In this paper, we consider a path exposure problem in energy harvesting wireless sensor networks (EH-WSNs) where nodes are equipped with directional communication devices. Nodes harvest energy from ambient environment (e.g., solar power), and manage fluctuations in their stored energy by adjusting some of their directional transmission parameters. Using a probabilistic graph model we formalize a problem, denoted DirEXPO-RU, that quantifies the ability of a network to detect and report traversal along a given path as probability representing the reliability of the network in performing the path monitoring task. A problem that arises in managing the network resources to maximize this reliability measure is to adjust the transmission beam width of each node, given that nodes beam centers are given as input. We develop a heuristic algorithm to deal with the problem, and use the algorithm in a framework for computing lower bounds on the reliability of the overall network. The obtained numerical results show improvement in the achieved network reliability.
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Short Papers
Paper Nr: 35
Title:

Reaction-Diffusion Inspired Sensor Networking: From Theory to Application
Authors:

Shu-Yuan Wu, Theodore Brown and Hsien-Tseng Wang
Abstract: Alan Turing introduced a novel Reaction-Diffusion (RD) model in 1952 to explain biological pattern formation found in animals. Since then, studies based on the RD model have long proved the feasibility of adapting it to spatial patern formation in distributed systems, especially in networking systems. In the past two decades, RD mechanism started being applied to Wireless Sensor Networks, and the possiblity of expanding to new applications is promising. In this paper, we first review the original RD model and further show its variants, known as activator-inhibitor models. Several research efforts on applying them to model tasks in wireless sensor networks will be presented and summarized.
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Paper Nr: 19
Title:

A New Architecture Proposal of Half-wave Precision Rectifier using a Single VCII
Authors:

Leila Safari, Gianluca Barile, Mattia Ragnoli, Giuseppe Ferri and Vincenzo Stornelli
Abstract: In this paper a new second generation voltage conveyor (VCII) based half wave rectifier circuit architecture proposal is presented. Both inverting and non-inverting outputs in the form of voltage signal are produced. The proposed circuit is the first half wave rectifier architecture using VCIIs introduced in the literature. It consists of one VCII, two diodes and a single grounded resistor. The input signal is in current form and the rectified output voltage signal is provided at the low impedance Z port of the same VCII. Therefore, the produced output signal can be directly used with no need to add extra voltage buffers. In addition, the circuit gain is set by the grounded resistor value and can be tuned. The proposed circuit enjoys a simple transistor- level structure employing only 21 transistors. In this paper, the architecture of the rectifier is presented and explained, as well as a possible VCII topology. Preliminary simulation results are also given highlighting its capabilities. Its simplicity and versatility make it suitable for sensor interfaces and processing circuits for sensor networks where a low power consumption for the analog processing section is of the utmost importance.
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Area 3 - Sensor Networks Applications

Full Papers
Paper Nr: 24
Title:

A Wireless Low-power System for Digital Identification of Examinees (Including Covid-19 Checks)
Authors:

Danilo Weber Nunes and Klaus Volbert
Abstract: Indoor localization has been, for the past decade, a subject under intense development. There is, however, no currently available solution that covers all possible scenarios. Received Signal Strength Indicator (RSSI) based methods, although the most widely researched, still suffer from problems due to environment noise. In this paper, we present a system using Bluetooth Low Energy (BLE) beacons attached to the desks to localize students in exam rooms and, at the same time, automatically register them for the given exam. By using Kalman Filters (KFs) and discretizing the location task, the presented solution is capable of achieving 100% accuracy within a distance of 45cm from the center of the desk. As the pandemic gets more controlled, with our lives slowly transitioning back to normal, there are still sanitary measures being applied. An example being the necessity to show a certification of vaccination or previous disease. Those certifications need to be manually checked for everyone entering the university’s building, which requires time and staff. With that in mind, the automatic check for Covid certificates feature is also built into our system.
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Paper Nr: 37
Title:

Analysis of RPL Objective Functions with Security Perspective
Authors:

Cansu Dogan, Selim Yilmaz and Sevil Sen
Abstract: The IPv6 Routing Protocol for Low Power Lossy Networks (RPL) is one of the standardized routing protocols for lossy networks consisting of resource-constrained Internet of Things (IoT) devices. RPL allows to use different objective functions based on different routing metrics such as expected transmission count (ETX), hop count, and energy to determine effective routes. In the literature, the performance of two objective functions namely Objective Function Zero (OF0), Minimum Rank with Hysteresis Objective Function (MRHOF) are evaluated thoroughly, since they are accepted as standard objective functions in RPL. However their performance under attack has not been evaluated comprehensively yet. Although RPL has defined some specifications for its security, it is still vulnerable to insider attacks, which could dramatically affect the network performance. Therefore, this study investigates how the performance of objective functions are affected by RPL specific attacks. Version number, DIS flooding, and worst parent attacks are analyzed by using the following performance metrics: packet delivery ratio, overhead, latency, and power consumption. Moreover, how they are affected by the number of attackers in the network are analyzed. To the best of the authors’ knowledge, this is the first study that comprehensively explores RPL objective functions on networks under attacks.
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Paper Nr: 38
Title:

Snowflake: An Adaptive Energy and Delay Efficient Scheme for Source Location Privacy in Wireless Sensor Networks
Authors:

Sain Saginbekov and Dossay Oryspayev
Abstract: Wireless Sensor Networks (WSNs) consist of a number of resource-constrained sensor nodes and a designated node called a sink, which collects data from the sensor nodes. A WSN can be used in numerous applications such as subject tracking and monitoring, where it is often desirable to keep the location of the subject private. In these types of applications, an adversary can locate the monitored subject, if a location privacy protection scheme is not applied. In this paper, we propose an adaptive energy and delay efficient scheme, called Snowflake, that conceals the location of subjects from a global adversary. Snowflake can be adapted to make the delivery delay smaller, or to make the packet overhead low. The simulation results show that Snowflake performs better than an existing algorithm.
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Short Papers
Paper Nr: 4
Title:

Designing a Real-time IoT Data Streaming Testbed for Horizontally Scalable Analytical Platforms: Czech Post Case Study
Authors:

Martin Štufi and Boris Bačić
Abstract: There is a growing trend for enterprise-level Internet of Things (IoT) applications requiring real-time horizontally scalable data processing platforms. Real-time processing platforms receiving data streams from sensor networks (e.g., autonomous and connected vehicles, smart security for businesses and homes, smartwatches, fitness trackers, and other wearables) require distributed MQTT brokers. This case study presents an IoT data streaming testbed platform prepared for the Czech Post. The presented platform has met the throughput requirement of 2 million messages per 24 hours (comprising SMS and emails). The tested MQTT broker runs on a single virtual node of a horizontally scalable testbed platform. Soon the Czech Post will modernise its eServices to increase package deliveries aligned with eCommerce and eGovernment demands. The presented testbed platform fulfils all requirements, and it is also capable of processing thousands of messages per second. The presented platform and concepts are transferable to healthcare systems, transport operations, the automotive industry, and other domains such as smart cities.
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Paper Nr: 8
Title:

IoT Application for Monitoring and Storage of Temperature History in Electric Motors
Authors:

Jairovan Denis de Paiva, Carlos Roberto da Silveira Junior and Arquimedes Lopes da Silva
Abstract: The three-phase induction motor is the most used type of motor. It is estimated that more than 90% of the mechanical energy used in industry is supplied by three-phase induction motors. Therefore, an early and unexpected failure of an electric motor is quite costly to the industry. This paper aims to present the development of an IoT (Internet of Things) application for monitoring and storing the operating temperature history of three-phase electric motors through a wireless sensor network. Real-time temperature values, peak temperature values, tables and graphics of internal engine temperatures are displayed from web pages. Two 1200 HP motors were monitored. The temperatures were obtained through PT100 transducers installed in the motor windings and the ambient temperature read by a digital sensor. The data read by the sensors is kept in a database in the clouds, in order to generate relevant information to support the maintenance management of these assets. Part of the application processing is performed in the clouds, such as the parameterization of the microcontroller program and sending notifications via email, for cases of reading failure, communication failure and high temperature alert. The results demonstrate the applicability and functionality of the application in an industrial environment, allowing the identification of various engine behaviors over time.
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Paper Nr: 10
Title:

Cryptanalysis of an Anonymous Mutual Authentication Protocol for Wireless Body Area Network
Authors:

Azeddine Attir
Abstract: Wireless body area networks (WBANs) represent an important entity in E-health system, these networks offer enhanced efficiency, flexibility, and cost savings to patients, healthcare providers, and medical professionals in home- as well as hospital-based scenarios. The authentication of sensors is an essential security task. To the best of our knowledge, (Li et al, 2017) proposed the lightest authentication and key agreement scheme for WBAN. However, (M. Koya and Deepthi P. P, 2018) show that the Li et al. scheme is vulnerable to impersonation attack and they proposed to use the biokeys extracted from the inter pulse interval (IPI) to defend this attack. In this paper, we demonstrate that the M. Koya and Deepthi P. P scheme is vulnerable from sensor node spoofing attack hence, it does not provide anonymity. Subsequently we propose a security solution tackled with such vulnerability.
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Paper Nr: 25
Title:

Wireless Sensor Network for Environmental Monitoring of Cultural Heritage
Authors:

Adrián Hinostroza and Jimmy Tarrillo
Abstract: Cultural heritage assets represent the history and unique identity for every nation in the world, so their protection and conservation are mandatory tasks. However, although such assets are usually exhibited in special museum rooms, sometimes the environmental conditions may be modified, putting the materials at risk. These facts can be more severe in warehouses, where environmental conditions can vary even more. Most of the measurement sites are located in spaces that make it difficult or do not allow the handling of commercial devices for measuring multiple environmental parameters, either due to their size, energy consumption or because they cannot be connected to the internet, so there is no timely availability of information on the environmental condition in which they are found. This work presents the design and implementation of a wireless sensors network based on Bluetooth Low Energy and ZigBee, able to measure temperature, moisture, light intensity and irradiance, and particulate matter 2.5 and 10, in the different spaces where objects of cultural heritage are found. These measurements are sent to a web platform through the use of Wi-Fi or GPRS technology.
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Paper Nr: 34
Title:

Real-time Approach for Decision Making in IoT-based Applications
Authors:

Hassan Harb, Diana Abi Nader, Kassem Sabeh and Abdallah Makhoul
Abstract: Nowadays, the IoT applications benefit widely many sectors including healthcare, environment, military, surveillance, etc. While the potential benefits of IoT are real and significant, two major challenges remain in front of fully realizing this potential: limited sensor energy and decision making in real-time applications. To overcome these problems, data reduction techniques over data routed to the sink should be used in such a way that they do not discard useful information. In this paper, we propose a new energy efficient and real-time based algorithm to improve the decision making in IoT. At first data reduction is applied at the sensor nodes to reduce their raw data based on a predefined scoring system. Then, a second data reduction phase is applied at intermediate nodes, called grid leaders. It uses K-means as a clustering algorithm in order to eliminate data redundancy collected by the neighbor nodes. Finally, decision is taken at the sink level based on a scoring risk system and a risk-decision table. The evaluation of our technique is made based on a simulation from data collected on sensors at Intel Berkeley research lab. The obtained results show the relevance of our technique, in terms of data reduction and energy consumption.
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Paper Nr: 5
Title:

Infrared Photoelectric Sensor Network Applied to Remote Arthropod Insects’ Surveillance
Authors:

Federico Gaona, Ever Quiñonez, Adolfo Jara, Ariel Manabe, Norma Silva, Magna Monteiro, Christian E. Schaerer, María Celeste Vega and Antonieta Rojas de Arias
Abstract: This work presents a monitoring system trap to detect the presence of arthropod insects in a remote surveillance zone. Detections are made using sensor traps that are installed in twenty houses of an indigenous village of the Paraguayan Chaco in South America, where the insects that transmit Chagas disease are pressing to infest the area. Pheromone baits are used to ensure the attraction of Triatoma infestans. For detecting variations of the light due to insect intrusion, trap entrances have photoelectric infrared sensors. Once the insect is detected, the information is collected and transmitted to an Internet database storage server. More than 750 intrusions were detected during nine months, the highest number of detections occurred when the temperature ranged between 20 C̊ and 34 C̊, relative humidity average less than 30% and the precipitation was less than 1.5 mm. This new result provides evidence of the T. infestans activity at different times of the day and month, and its relationship with certain environmental variables. These findings contribute to reorientate surveillance procedures, validate the monitoring system proposal and give important information on the vector's life activity.
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Paper Nr: 12
Title:

MASHCA: Monitoring and Hydro Climatological Analysis of the Urban Microclimate of Latacunga
Authors:

David Rivas-Lalaleo, Alex Santana G., Cristian Molina, Mónica Huerta, Roger Clotet, Andrés Pérez, Luis Santana and Fernanda Oñate
Abstract: The climate change has become one of the most studied problems in recent years. Analyses of climate behavior have traditionally been treated in a macro way, that is, large areas of territory are analyzed. The development of humanity in particular, which has been denoted by the increase in population and therefore the growth of cities, has had an effect on the climate. The change in climatic conditions within cities due to the effects of construction, urban planning, modification of territories, among others, are known as urban micro-climates. These variations require special attention, since these apparently minimal changes can have a great effect on the life of the population. The purpose of this project is to study the historical data on the behavior of the urban climate of Latacunga, through the temporal analysis of the data obtained by the meteorological station of the Universidad de las Fuerzas ESPE, later to develop micro meteorological stations that are installed in various locations of the city, finally the information generated and its corresponding reports will be presented through a web page, thus allowing to have a tool that allows to identify the behavior of the urban microclimate of the city of Latacunga. The results obtained have made it possible to identify the maximum, minimum and most frequent values of temperature, humidity, speed and wind direction. In addition, with the installation of the new stations, the monitoring of variables such as solar radiation, atmospheric pressure, among others, has increased. With the information processed, it will allow the generation of recommendations oriented to risk management, urban planning and citizen security.
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Paper Nr: 13
Title:

Modeling of Energy Consumption for Wired Access Control Systems
Authors:

M. Oussayran, J.-C. Prévotet, J.-Y. Baudais and A. Maiga
Abstract: Access control systems consist in managing access to buildings or any secure area where access is restricted. This paper presents a model that helps build access control systems along with its internal architecture. This system is modeled according to the behavior of the access control system. The OMNeT++ network simulator, in addition to the INET framework, is used to model the behavior of a studied system as well as its energy consumption. The paper aims to compare the energy consumption of the studied system and its simulated model with the same working scenario. The challenge is to create a simulation model with a set of configurable parameters, where users will be able to modify the value of the latter, based on the intended application. By this way, the simulated model calculates promptly the energy consumption.
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Paper Nr: 26
Title:

Flexigy Smart-grid Architecture
Authors:

Tiago Fonseca, Luis Lino Ferreira, Lurian Klein, Jorge Landeck and Paulo Sousa
Abstract: The electricity field is facing major challenges in the implementation of Renewable Energy Sources (RES) at a large scale. End users are taking on the role of electricity producers and consumers simultaneously (prosumers), acting like Distributed Energy Resources (DER), injecting their excess electricity into the grid. This challenges the management of grid load balance, increases running costs, and is later reflected in the tariffs paid by consumers, thus threatening the widespread of RES. The Flexigy project explores a solution to this topic by proposing a smart-grid architecture for day-ahead flexibility scheduling of individual and Renewable Energy Community (REC) resources. Our solution is prepared to allow Transmission System Operators (TSO) to request Demand Response (DR) services in emergency situations. This paper overviews the grid balance problematic, introduces the main concepts of energy flexibility and DR, and focuses its content on explaining the Flexigy architecture.
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Paper Nr: 28
Title:

A Novel Energy-efficient Wormhole Attack Prevention Protocol for WSN based on Trust and Reputation Factors
Authors:

Saad Al-Ahmadi
Abstract: The deployment of Wireless Sensor Networks (WSNs) for the Internet of Things (IoT) is important, but this also poses some security issues. Wireless Sensor Networks (WSNs) are vulnerable to various attacks, such as the Wormhole attack. The Wormhole attack is one of the most severe attacks on WSNs that is particularly challenging to defend against even when the communication is authentic, and sensors are not compromised. Existing techniques to detect and protect against Wormhole attacks place a substantial burden on the scarce sensor resources and do not consider the dynamic nature of the network. In this paper, a novel Energy Efficient Wormhole Attack Prevention Protocol (EWATR) is proposed to protect WSNs against Wormhole attacks. EWATR is based on trust and reputation among WSN nodes that consider the dynamic nature of the network. This study also compares EWATR against several state-of-the-art trust and reputation models through extensive simulations using the TRMSim-WSN simulator. Eventually, the simulation results show the superiority of EWATR over other proposed protocols in terms of efficient energy consumption and shorter path length.
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Paper Nr: 29
Title:

Underwater Wireless Sensor Networks: A Review
Authors:

Mohammad Alsulami, Rafaat Elfouly and Reda Ammar
Abstract: Several disciplines like science, engineering, and biological industry have been influenced by sensor networks which have brought sensing and computation into reality. The possibility of having these sensors physically assigned close to the target whose parameters are to be observed enables remote monitoring of various aspects of the physical world. Wireless channeling of information beneath the ocean or generally underwater has provided the best technological ways of oceanic observations. Ocean bottoms have been monitored traditionally by deploying oceanographic sensors that obtain information at distinct and fixed ocean zones. The oceanographic instruments are then recovered when the tasks are completed. This implies that data cannot be monitored remotely since there is no collaborative communication of obtained data between the collection point and the monitoring end. The data recorded can also be destroyed in case of a non-successful mission. Oceanic observations have been made primarily possible by sensor networks carefully laid out under the waters. Underwater sensor networks can also be achieved wirelessly by establishing communications between sensors and monitors without major cabling. These are known as Underwater Wireless Sensor Networks (UWSNs). The UWSNs are comprised of various gadgets like vehicles that can operate autonomously under the water and sensors. Deployment of these gadgets is done in targeted acoustic zones for the collection of data and monitoring tasks. Bilateral communication is established between stations based on the ground and different UWSNs nodes. This enables instantaneous remote monitoring and communication of information from the specified oceanic zones to engineering personnel based on the shores. This paper looks at the various aspects of Underwater Wireless Sensor Networks UWSNs including their importance, applications, network architecture, requirements, and challenges and in their deployments.
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Paper Nr: 33
Title:

An Application with Jetson Nano for Plant Stress Detection and On-field Spray Decision
Authors:

Marcos A. de Oliveira Jr., Gregory Sedrez, Guilherme de Souza and Gerson Geraldo H. Cavalheiro
Abstract: Increasing field productivity is not just a financial need, but also a social issue. Several technologies converge to promote food production and, in this context, the fog computing paradigm can support the development of solutions for precision agriculture. This paper proposes an application of the Jetson Nano device, embedded in an agricultural spraying implement. This device supports the decision on irrigation activity, based on data collected by sensors distributed in the field. The sensors read information about the plant’s stress level from electrical signals and the Jetson Nano enables real-time analysis, through machine learning algorithms, to manage the product spray rate, according to the condition of the crop. Initial studies validated the proposed solution on an experimental basis, showing that the device can be an alternative for this purpose, since it can be used efficiently in machine learning tasks from data collected by the sensors. The experiment also highlighted some limitations of the proposed solution, such as the importance of observing the conditions of the system as a whole, its context and environment, in order to improve performance in spraying process.
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Paper Nr: 36
Title:

Genetic Programming based Algorithm for HW/SW Cosynthesis of Distributed Embedded Systems Specified using Conditional Task Graph
Authors:

Adam Górski and Maciej Ogorzałek
Abstract: In this paper we propose a novel genetic programming based iterative improvement approach for hardware/software cosynthesis of distributed embedded systems. Unlike other genetic programming solutions for distributed embedded systems in this work the system is specified using conditional task graph. In such a graph every node represents a single task. The edge represents amount of data needed to be transferred between connected tasks, however some of the edges can be conditional. The data is transferred using those edges only if condition is satisfied. Proposed methodology is based on genetic programming. Therefore the genotype is a system construction tree. In each nodes of the tree are system building options. The next generations are obtained using standard genetic operators: mutation, crossover, cloning and selection.
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