Kids make their own robots: good practices from the eCraft2Learn project

This paper focuses on the small-scale pilots with learners that were carried out in Greece in the frame of the eCraft2Learn project including activities that aim at reinforcing learning by making in STEAM education. In the context of the pilots, 13-17 years-old students worked with digital fabrication and making technologies for creating robotic artefacts. In the framework of an appropriate pedagogical model that supports different steps highly interlinked, the teachers and students were invited to work together and explore the fun and the challenges of the making process using the eCraft2Learn learning ecosystem. In this line, a number of good practices were identified related to the facilitation of the learning process, the support of the ideation, the boosting of the can-do attitude, the embracement of failure and the encouragement towards sharing projects, experiences and ideas. Most of these practices are reflected in video-recorded episodes accessible through this paper. I bambini creano i propri robot: buone pratiche dal progetto eCraft2LearnIl presente lavoro documenta le prime applicazioni realizzate in Grecia, nell’ambito del progetto eCraft2Learn, dedicato a rafforzare la formazione nell’area STEAM con il learning by making. Studenti tra i 13 e i 17 anni hanno applicato tecnologie digitali e tecniche artigianali per creare artefatti robotici. Nell’ambito di un modello pedagogico appropriato, in grado di supportare diversi passi altamente interconnessi tra loro, i docenti e gli studenti sono stati invitati a lavorare insieme e ad esplorare gli aspetti di divertimento e di sfida relativi al processo creativo utilizzando l’ecosistema di apprendimento eCraft2Learn. Nel progetto sono state identificate una serie di buone pratiche relative alla facilitazione del processo di apprendimento, al supporto all’ideazione, al rinforzo di un atteggiamento positivo, all’accettazione del fallimento e all’incentivazione della condivisione di progetti, esperienze, idee. La maggior parte di queste pratiche sono state video registrate e sono rese accessibili attraverso il presente articolo

Extending Smart Phone Based Techniques to Provide AI Flavored Interaction with DIY Robots, over Wi-Fi and LoRa interfaces

Inspired by the mobile phone market boost, several low cost credit card-sized computers have made the scene, able to support educational applications with artificial intelligence features, intended for students of various levels. This paper describes the learning experience and highlights the technologies used to improve the function of DIY robots. The paper also reports on the students’ perceptions of this experience. The students participating in this problem based learning activity, despite having a weak programming background and a confined time schedule, tried to find efficient ways to improve the DIY robotic vehicle construction and better interact with it. Scenario cases under investigation, mainly via smart phones or tablets, involved from touch button to gesture and voice recognition methods exploiting modern AI techniques. The robotic platform used generic hardware, namely arduino and raspberry pi units, and incorporated basic automatic control functionality. Several programming environments, from MIT app inventor to C and python, were used. Apart from cloud based methods to tackle the voice recognition issues, locally running software alternatives were assessed to provide better autonomy. Typically, scenarios were performed through Wi-Fi interfaces, while the whole functionality was extended by using LoRa interfaces, to improve the robot’s controlling distance. Through experimentation, students were able to apply cutting edge technologies, to construct, integrate, evaluate and improve interaction with custom robotic vehicle solutions. The whole activity involved technologies similar to the ones making the scene in the modern agriculture era that students need to be familiar with, as future professionals

Traffic generation and analysis emphasized on ATM and IP network technologies

The information volume and the application variety are constantly increasing imposing new demands on the telecommunication networks. Due to these reasons the problem of efficient network design, monitoring and control is more apparent than ever. Traffic generation and/or analysis tools, if properly applied, can assist in finding suitable solutions. The PhD thesis focuses on the development and usage methods of similar tools and is structured in ten chapters. In the first chapter the main components of the QoS delivery problem are mentioned while the emerging need for sufficient traffic generation and/or analysis tools is justified. The second chapter presents in detail the main characteristics of the environment where the proposed tools may be used. This environment consists mainly of ATM and IP topologies. The emphasis is put on the similarities between the discussed different platforms. At chapter 3 starts the detailed description of the proposed tools. More specifically in chapter 3 an advanced software architecture for ATM traffic generation is presented. This architecture exploits a stable and reliable hardware so as to provide the generation of traffic flows compliant with high level traffic model specifications. The basic advantage of the proposed generator is that it guarantees a fast and accurate traffic generation process. The software part introduces several innovations towards minimizing speed and memory constrains related to the hardware. Chapter 4 is dedicated to the presentation of the software supporting a prototype ATM traffic analyzer. The software exploits the experience acquired during the implementation of the ATM traffic generator counterpart. The software architecture of the proposed ATM analyzer exploits and controls the enhanced capabilities of the promising underlying hardware module the role of which is expanded in order to provide real time QoS metrics at relatively low computational cost. Apart from this, the software architecture directly creates models containing some cases of traffic being monitored. In chapter 5, an IP traffic generator is described. The remarkably successful use of the prototype ATM traffic generator, in conjunction with its well-balanced architecture led to the adoption of the presented generator’s logic in IP environments as well. It must be noticed that the whole effort does not ignore the idiosyncrasies of the Internet. The IP traffic generator, despite the simplicity of its first version, was proved as very useful to many testing cases where the exact reproduction of captured traffic was crucial or the hiring of real sources too expensive or complicated. Chapter 6 is dedicated to the description of traffic analyzers, especially designed for IP networks. As a first attempt, the ATM analyzer engine was further exploited, after the necessary modifications in its software architecture, while a sufficient «IP over ATM» mechanism was hired. At next stage, a native IP analyzer was designed and implemented. The later tool hires external clock units for solving the synchronization problem between source and destination nodes. The capabilities the two analyzers can be enhanced by injecting appropriate monitoring traffic into the network under evaluation. The «IP over ATM» based IP analyzer is capable of performing accurate and fast real time measurements without overloading the hosting system. One of its main advantages is the direct delivery of histograms presenting the inter-packet distance (or the packet size) distribution. The proposed native IP analyzer solves the problem performing real time reliable measurements of end-to-end delays or losses of IP packets. Chapter 7 is dedicated to another group of performance evaluation tools that work under looser real time constrains. They perform post-processing using log files captured by various traffic analysis tools. Via post-processing more testing cases can be assessed while more complex metrics can be incorporated into the analyzer’s logic. The computational load required for measurement processing is completely disconnected from the relevant load for data gathering. Chapter 8 presents an analyzer tool that is based on the logging capabilities exhibited by advanced network elements. Although the proposed tool does not differ in its high level architecture from the other traffic analysis tools being presented, data uploading mechanism is based on the SNMP MIBs supported by network elements like an IP router or an ATM switch. The specific tool is targeted towards assisting the rest of the analyzers. The main advantage of this tool is its flexibility as it can be transferred easily from one network platform to another. Chapter 9 presents several characteristic cases where the proposed tools are involved. Indeed, traffic generation and analysis tools have been exhaustively tested during a large number of experiments. The easy use of the tools and the complementarity of their features led to the appropriate solutions very fast in all cases. Furthermore, all the tools are cost-effective. The experiments being performed indicated for one more time that there are no solutions that are both integral and optimal, but only partial ones implied by the promised QoS and cost requirements. Finally, chapter 10 summarizes the thesis’s innovative points and contribution and indicates some open issues for further research

New Results for the Error Rate Performance of LoRa Systems over Fading Channels

Long Range (LoRa) systems have recently attracted significant attention within the research community as well as for commercial use due to their ability to transmit data over long distances at a relatively low energy cost. In this study, new results for the bit error rate performance of Long Range (LoRa) systems operating in the presence of Rayleigh, Rice, Nakagami-m, Hoyt, η-μ and generalized fading channels are presented. Specifically, we propose novel exact single integral expressions as well as simple, accurate expressions that yield tight results in the entire signal-to-noise ratio (SNR) region. The validity of our newly derived formulas is substantiated by comparing numerically evaluated results with equivalent ones, obtained using Monte-Carlo simulations and exact analytical expressions

Enhanced Robots as Tools for Assisting Agricultural Engineering Students’ Development

Inevitably, the rapid growth of the electronics industry and the wide availability of tailored programming tools and support are accelerating the digital transformation of the agricultural sector. The latter transformation seems to foster the hopes for tackling the depletion and degradation of natural resources and increasing productivity in order to cover the needs of Earth’s continuously growing population. Consequently, people getting involved with modern agriculture, from farmers to students, should become familiar with and be able to use and improve the innovative systems making the scene. At this point, the contribution of the STEM educational practices in demystifying new areas, especially in primary and secondary education, is remarkable and thus welcome, but things become quite uncertain when trying to discover efficient practices for higher education, and students of agricultural engineering are not an exception. Indeed, university students are not all newcomers to STEM and ask for real-world experiences that better prepare them for their professional careers. Trying to bridge the gap, this work highlights good practices during the various implementation stages of electric robotic ground vehicles that can serve realistic agricultural tasks. Several innovative parts, such as credit card-sized systems, AI-capable modules, smartphones, GPS, solar panels, and network transceivers are properly combined with electromechanical components and recycled materials to deliver technically and educationally meaningful results

Applications of Artificial Intelligence in Fire Safety of Agricultural Structures

Artificial intelligence applications in fire safety of agricultural structures have practical economic and technological benefits on commercial agriculture. The FAO estimates that wildfires result in at least USD 1 billion in agriculture-related losses due to the destruction of livestock pasture, destruction of agricultural buildings, premature death of farm animals, and general disruption of agricultural activities. Even though artificial neural networks (ANNs), genetic algorithms (GAs), probabilistic neural networks (PNNs), and adaptive neurofuzzy inference systems (ANFISs), among others, have proven useful in fire prevention, their application is limited in real farm environments. Most farms rely on traditional/non-technology-based methods of fire prevention. The case for AI in agricultural fire prevention is grounded on the accuracy and reliability of computer simulations in smoke movement analysis, risk assessment, and postfire analysis. In addition, such technologies can be coupled with next-generation fire-retardant materials such as intumescent coatings with a polymer binder, blowing agent, carbon donor, and acid donor. Future prospects for AI in agriculture transcend basic fire safety to encompass Society 5.0, energy systems in smart cities, UAV monitoring, Agriculture 4.0, and decentralized energy. However, critical challenges must be overcome, including the health and safety aspects, cost, and reliability. In brief, AI offers unlimited potential in the prevention of fire hazards in farms, but the existing body of knowledge is inadequate

Enhanced Robots as Tools for Assisting Agricultural Engineering Students’ Development

Inevitably, the rapid growth of the electronics industry and the wide availability of tailored programming tools and support are accelerating the digital transformation of the agricultural sector. The latter transformation seems to foster the hopes for tackling the depletion and degradation of natural resources and increasing productivity in order to cover the needs of Earth’s continuously growing population. Consequently, people getting involved with modern agriculture, from farmers to students, should become familiar with and be able to use and improve the innovative systems making the scene. At this point, the contribution of the STEM educational practices in demystifying new areas, especially in primary and secondary education, is remarkable and thus welcome, but things become quite uncertain when trying to discover efficient practices for higher education, and students of agricultural engineering are not an exception. Indeed, university students are not all newcomers to STEM and ask for real-world experiences that better prepare them for their professional careers. Trying to bridge the gap, this work highlights good practices during the various implementation stages of electric robotic ground vehicles that can serve realistic agricultural tasks. Several innovative parts, such as credit card-sized systems, AI-capable modules, smartphones, GPS, solar panels, and network transceivers are properly combined with electromechanical components and recycled materials to deliver technically and educationally meaningful results

Enriching IoT Modules with Edge AI Functionality to Detect Water Misuse Events in a Decentralized Manner

The digital transformation of agriculture is a promising necessity for tackling the increasing nutritional needs of the population on Earth and the degradation of natural resources. Focusing on the “hot” area of natural resource preservation, the recent appearance of more efficient and cheaper microcontrollers, the advances in low-power and long-range radios, and the availability of accompanying software tools are exploited in order to monitor water consumption and to detect and report misuse events, with reduced power and network bandwidth requirements. Quite often, large quantities of water are wasted for a variety of reasons; from broken irrigation pipes to people’s negligence. To tackle this problem, the necessary design and implementation details are highlighted for an experimental water usage reporting system that exhibits Edge Artificial Intelligence (Edge AI) functionality. By combining modern technologies, such as Internet of Things (IoT), Edge Computing (EC) and Machine Learning (ML), the deployment of a compact automated detection mechanism can be easier than before, while the information that has to travel from the edges of the network to the cloud and thus the corresponding energy footprint are drastically reduced. In parallel, characteristic implementation challenges are discussed, and a first set of corresponding evaluation results is presented

Using Open Tools to Transform Retired Equipment into Powerful Engineering Education Instruments: A Smart Agri-IoT Control Example

People getting involved with modern agriculture should become familiar with and able to exploit the plethora of cutting-edge technologies that have recently appeared in this area. The contribution of the educational robotics in demystifying new scientific fields for K-12 students is remarkable, but things become more challenging when trying to discover efficient practices for higher education. Indeed, there is an apparent need for pilot examples facilitating students’ professional skills acquisition and thus matching the potential of the actual systems used in the modern agricultural premises. In this regard, this work discuses laboratory experiences while implementing an automatic airflow control system of convincing size and role capable for remote configuration and monitoring. This non-conventional robotic example exploits retired electromechanical equipment, from an old farm, and revives it using modern widely available microcontrollers, smart phones/tablets, network transceivers, motor drivers, and some cheap and/or custom sensors. The contribution of the corresponding software parts to this transformation is of crucial importance for the success of the whole system. Thankfully, these parts are implemented using easy-to-use programming tools, of open and free nature at most, that are suitable for the pairing credit-card-sized computer systems. The proposed solution is exhibiting modularity and scalability and assists students and future professionals to better understand the role of key elements participating in the digital transformation of the agricultural sector. The whole approach has been evaluated from both technical and educational perspective and delivered interesting results that are also reported

Using Open Tools to Transform Retired Equipment into Powerful Engineering Education Instruments: A Smart Agri-IoT Control Example

People getting involved with modern agriculture should become familiar with and able to exploit the plethora of cutting-edge technologies that have recently appeared in this area. The contribution of the educational robotics in demystifying new scientific fields for K-12 students is remarkable, but things become more challenging when trying to discover efficient practices for higher education. Indeed, there is an apparent need for pilot examples facilitating students’ professional skills acquisition and thus matching the potential of the actual systems used in the modern agricultural premises. In this regard, this work discuses laboratory experiences while implementing an automatic airflow control system of convincing size and role capable for remote configuration and monitoring. This non-conventional robotic example exploits retired electromechanical equipment, from an old farm, and revives it using modern widely available microcontrollers, smart phones/tablets, network transceivers, motor drivers, and some cheap and/or custom sensors. The contribution of the corresponding software parts to this transformation is of crucial importance for the success of the whole system. Thankfully, these parts are implemented using easy-to-use programming tools, of open and free nature at most, that are suitable for the pairing credit-card-sized computer systems. The proposed solution is exhibiting modularity and scalability and assists students and future professionals to better understand the role of key elements participating in the digital transformation of the agricultural sector. The whole approach has been evaluated from both technical and educational perspective and delivered interesting results that are also reported