Yapay Zeka ve Nesnelerin İnternetine Dayalı Otomatik Sulama Sistemi

It is not hard to see that the need for clean water is growing by considering the decrease of the water sources day by day in the world. Potable fresh water is also used for irrigation, so it should be planned to decrease fresh water wastage. With the development of the technology and the availability of cheaper and more effective solutions, the efficiency of the irrigation increased and the water loss can be reduced. In particular, Internet of things (IoT) devices have begun to be used in all areas. We can easily and precisely collect temperature, humidity and mineral values from the irrigation field with the IoT devices and sensors. Most of the operations and decisions about irrigation are carried out by people. For people, it is hard to have all the real time data such as temperature, moisture and mineral levels in the decision-making process and make decisions by considering them. People usually make decisions with their experience. In this study, a wide range of information from irrigation field was obtained by using IoT devices and sensors. Data collected from IoT devices and sensors sent via communication channels and stored on MongoDB.With the help of Weka software, the data was normalized and the normalized data was used as a learning set. As a result of the examinations, decision tree (J48) algorithm with the highest accuracy was chosen and artificial intelligence model was created. Decisions are used to manage operations such as starting, maintaining and stopping the irrigation. The accuracy of the decisions was evaluated and the irrigation system was tested with the results. There are options to manage, view the system remotely and manually and also see the system’s decisions with the created mobile application.Dünyadaki temiz su kaynaklarının günden güne azalması göz önüne alındığında temiz su ihtiyacının arttığını görmek zor değildir. Temiz içme suyu aynı zamanda sulama için de kullanılır bu nedenle temiz su israfı azaltma süreci planlanmalıdır. Teknolojinin gelişmesi, daha ucuz ve daha etkin çözümlerin ortaya çıkması ile birlikte, sulama verimliliği artmakta ve su kaybı azalmaktadır. Özellikle, Nesnelerin İnterneti cihazları (IoT) tüm alanlarda kullanılmaya başlanmıştır. IoT cihazlar ve sensörler ile sulama alanından sıcaklık, nem ve mineral değerlerini kolayca ve hassas bir şekilde toplayabiliriz. Günümüzde sulama ile ilgili işlem ve kararların çoğu insanlar tarafından yürütülmektedir. Karar verme sürecinde sıcaklık, nem ve mineral seviyeleri gibi birçok gerçek zamanlı veriye sahip olmak ve bunları dikkate alarak karar vermek insanlar için zordur. İnsanlar genellikle kendi deneyimleriyle karar alırlar. Bu çalışmada, IoT cihazları ve sensörler kullanılarak sulama alanından geniş bir veri toplanmıştır. IoT cihazlarından ve sensörlerden toplanan veriler, iletişim kanallarından sunucuya aktarılır ve MongoDB üzerinde saklanır. Weka yazılımı yardımı ile normalizasyon işlemleri yapılan veriler öğrenme seti olarak kullanılır. Denemeler sonucunca yüksek başarı oranına sahip karar ağacı (J48) algoritması seçilmiş ve yapay zeka modeli oluşturulmuştur. Kararlar, sulamayı başlatmak, sürdürmek ve durdurmak gibi işlemleri yönetmek için kullanılmıştır. Kararların doğruluğu değerlendirilmiş ve sulama sistemi sonuçlarla test edilmiştir. Oluşturulan mobil uygulama ile sistemi uzaktan ve manuel olarak yönetmek, görüntülemek ve ayrıca sistemin vermiş olduğu kararları görebilmek için seçenekler vardır

Thermal conductivity engineering of bulk and one-dimensional Si-Ge nanoarchitectures

Various theoretical and experimental methods are utilized to investigate the thermal conductivity of nanostructured materials; this is a critical parameter to increase performance of thermoelectric devices. Among these methods, equilibrium molecular dynamics (EMD) is an accurate technique to predict lattice thermal conductivity. In this study, by means of systematic EMD simulations, thermal conductivity of bulk Si-Ge structures (pristine, alloy and superlattice) and their nanostructured one dimensional forms with square and circular cross-section geometries (asymmetric and symmetric) are calculated for different crystallographic directions. A comprehensive temperature analysis is evaluated for selected structures as well. The results show that one-dimensional structures are superior candidates in terms of their low lattice thermal conductivity and thermal conductivity tunability by nanostructuring, such as by diameter modulation, interface roughness, periodicity and number of interfaces. We find that thermal conductivity decreases with smaller diameters or cross section areas. Furthermore, interface roughness decreases thermal conductivity with a profound impact. Moreover, we predicted that there is a specific periodicity that gives minimum thermal conductivity in symmetric superlattice structures. The decreasing thermal conductivity is due to the reducing phonon movement in the system due to the effect of the number of interfaces that determine regimes of ballistic and wave transport phenomena. In some nanostructures, such as nanowire superlattices, thermal conductivity of the Si/Ge system can be reduced to nearly twice that of an amorphous silicon thermal conductivity. Additionally, it is found that one crystal orientation, $$, is better than the $$ crystal orientation in one-dimensional and bulk SiGe systems. Our results clearly point out the importance of lattice thermal conductivity engineering in bulk and nanostructures to produce high-performance thermoelectric materials

Authentication in Internet of Things Systems via Mobile Communication Technologies

The Internet of things (IoT) has become a popular workplace that has been used frequently nowadays. The message queue telemetry transport (MQTT) protocol, which is used in communication of devices with each other without human interactions, is preferred in this study because it is advantageous with its minimum data size and more message transmission with high bandwidth in IoT scenarios. In addition to the username and password authentication features that exist in the MQTT protocol, (one-time password - OTP) has been generated to provide device authentication via the global system for mobile communications (GSM) technology over different communication channel by considering the restriction of devices to operate and avoiding encryption algorithms that require heavy computation. The aim of the scope of this study, security is provided that in case of there is no secure channel between client and server, system is not accessible since OTP is not validated by the user even if username and password are obtained by attacker

Validation of inter-atomic potential for WS2 and WSe2 crystals through assessment of thermal transport properties

In recent years, transition metal dichalcogenides (TMDs) displaying astonishing properties are emerged as a new class of two-dimensional layered materials. The understanding and characterization of thermal transport in these materials are crucial for efficient engineering of 2D TMD materials for applications such as thermoelectric devices or overcoming general overheating issues. In this work, we obtain accurate Stillinger-Weber type empirical potential parameter sets for single-layer WS2 and WSe2 crystals by utilizing particle swarm optimization, a stochastic search algorithm. For both systems, our results are quite consistent with first-principles calculations in terms of bond distances, lattice parameters, elastic constants and vibrational properties. Using the generated potentials, we investigate the effect of temperature on phonon energies and phonon linewidth by employing spectral energy density analysis. We compare the calculated frequency shift with respect to temperature with corresponding experimental data, clearly demonstrating the accuracy of the generated inter-atomic potentials in this study. Also, we evaluate the lattice thermal conductivities of these materials by means of classical molecular dynamics simulations. The predicted thermal properties are in very good agreement with the ones calculated from first-principles.TUBITAK (115F024); Anadolu University (BAP-1407F335 BAP-1705F335); BAGEP Award of the Science Academ

Thermal transport properties of MoS2 and MoSe2 monolayers

The isolation of single- to few-layer transition metal dichalcogenides opens new directions in the application of two-dimensional materials to nanoelectronics. The characterization of thermal transport in these new low-dimensional materials is needed for their efficient implementation, either for general overheating issues or specific applications in thermoelectric devices. In this study, the lattice thermal conductivities of single-layer MoS2 and MoSe2 are evaluated using classical molecular dynamics methods. The interactions between atoms are defined by Stillinger-Weber-type empirical potentials that are developed to represent the structural, mechanical, and vibrational properties of the given materials. In the parameterization of the potentials, a stochastic optimization algorithm, namely particle swarm optimization, is utilized. The final parameter sets produce quite consistent results with density functional theory in terms of lattice parameters, bond distances, elastic constants, and vibrational properties of both single-layer MoS2 and MoSe2. The predicted thermal properties of both materials are in very good agreement with earlier first-principles calculations. The discrepancies between the calculations and experimental measurements are most probably caused by the pristine nature of the structures in our simulations.Anadolu University (BAP-1407F335 -1505F200); NSF (DMR 0844082); US Department of Energy, Office of Science, Office of Basic Energy Sciences (DE-AC02-06CH11357); Turkish Academy of Sciences (TUBA-GEBIP