Energy savings are very common in IoT sensor networks because IoT sensor nodes operate with their own limited battery. The data transmission in the IoT sensor nodes is very costly and consume much of the energy while the energy usage for data processing is considerably lower. There are several energy-saving strategies and principles, mainly dedicated to reducing the transmission of data. Therefore, with minimizing data transfers in IoT sensor networks, can conserve a considerable amount of energy. In this research, a Compression-Based Data Reduction (CBDR) technique was suggested which works in the level of IoT sensor nodes. The CBDR includes two stages of compression, a lossy SAX Quantization stage which reduces the dynamic range of the sensor data readings, after which a lossless LZW compression to compress the loss quantization output. Quantizing the sensor node data readings down to the alphabet size of SAX results in lowering, to the advantage of the best compression sizes, which contributes to greater compression from the LZW end of things. Also, another improvement was suggested to the CBDR technique which is to add a Dynamic Transmission (DT-CBDR) to decrease both the total number of data sent to the gateway and the processing required. OMNeT++ simulator along with real sensory data gathered at Intel Lab is used to show the performance of the proposed technique. The simulation experiments illustrate that the proposed CBDR technique provides better performance than the other techniques in the literature.
The increased food requirement puts intense pressure on the agriculture community to grow more from the same resources resulting in people leaving the farming business. This happened not exclusively due to the industrial pressure to produce more but to the lack of technology adoption among growers. The use of the sensor in agriculture is not new, but its adoption among agriculture producers is a challenge for industry and scientists. This study aimed to determine sensors used in agricultural fields with challenges and prospects. The study found that sensors have successfully been used at the industry level with highly skilled labor; however, their adoption is challenging in rural agriculture systems due to the lack of a support
... Show MoreThis paper presents an efficient system using a deep learning algorithm that recognizes daily activities and investigates the worst falling cases to save elders during daily life. This system is a physical activity recognition system based on the Internet of Medical Things (IoMT) and uses convolutional neural networks (CNNets) that learn features and classifiers automatically. The test data include the elderly who live alone. The performance of CNNets is compared against that of state-of-the-art methods, such as activity windowing, fixed sample windowing, time-weighted windowing, mutual information windowing, dynamic windowing, fixed time windowing, sequence prediction algorithm, and conditional random fields. Th
... Show MoreApplications of remote sensing are important in improving potato production through the broader adoption of precision agriculture. This technology could be useful in decreasing the potential contamination of soil and water due to the over-fertilization of agriculture crops. The objective of this study was to assess the utility of active sensors (Crop Circle™, Holland Scientific, Inc., Lincoln, NE, USA and GreenSeeker™, Trimble Navigation Limited, Sunnyvale, CA, USA) and passive sensors (multispectral imaging with Unmanned Arial Vehicles (UAVs)) to predict total potato yield and phosphorus (P) uptake. The experimental design was a randomized complete block with four replications and six P treatments, ranging from 0 to 280 kg P ha−1, as
... Show MoreDeep learning techniques are applied in many different industries for a variety of purposes. Deep learning-based item detection from aerial or terrestrial photographs has become a significant research area in recent years. The goal of object detection in computer vision is to anticipate the presence of one or more objects, along with their classes and bounding boxes. The YOLO (You Only Look Once) modern object detector can detect things in real-time with accuracy and speed. A neural network from the YOLO family of computer vision models makes one-time predictions about the locations of bounding rectangles and classification probabilities for an image. In layman's terms, it is a technique for instantly identifying and recognizing
... Show Moreالمستخلص يهدف هذا البحث الى تجاوز مشكلة البعدية من خلال طرائق الانحدار اللامعلمي والتي تعمل على تقليل جذر متوسط الخطأ التربيعي (RMSE) , أذ تم استعمال طريقة انحدار الاسقاطات المتلاحقة (PPR) ,والتي تعتبر احدى طرائق اختزال الابعاد التي تعمل على تجاوز مشكلة البعدية (curse of dimensionality) , وان طريقة (PPR) من التقنيات الاحصائية التي تهتم بأيجاد الاسقاطات الاكثر أهمية في البيانات المتعددة الابعاد , ومع ايجاد كل اسقاط
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This research aim to overcome the problem of dimensionality by using the methods of non-linear regression, which reduces the root of the average square error (RMSE), and is called the method of projection pursuit regression (PPR), which is one of the methods for reducing dimensions that work to overcome the problem of dimensionality (curse of dimensionality), The (PPR) method is a statistical technique that deals with finding the most important projections in multi-dimensional data , and With each finding projection , the data is reduced by linear compounds overall the projection. The process repeated to produce good projections until the best projections are obtained. The main idea of the PPR is to model
... Show MoreThe systems cooling hybrid solar uses solar collector to convert solar energy into the source of heat for roasting Refrigerant outside of the compressor and this process helps in the transformation of Refrigerant from the gas to a liquid state in two-thirds the top of the condenser instead of two-thirds the bottom of the condenser as in Conventional cooling systems and this in turn reduces the energy necessary to lead the process of cooling. The system cooling hybrid use with a capacity of 1 ton and Refrigerant type R22 and the value of current drawn by the system limits (3.9-4.2A), the same value of electric current calculated by the system are Conventional within this atmosphere of Iraq, and after taking different readings
... Show MoreThis work investigates the utilization of waste papers (natural and industrial) i.e (citrus aurantium and papers A4) mortars containing specified contents 0.5%, 1%, 1.5% of waste papers were prepared and cured. Mechanical characteristics such as compressive and bending strengths, hardness and water absorption were determined for the mortars mixed with the waste papers and compared with those obtained from the pure mortars. Results showed that the addition of waste paper leads to increase the hardness to (69 - 68.5) shore D for (natural and industrial) wastes materials respectively comparing with pure specimen 66 shore D. The compressed strength of the mortar cement specimen cured for 28 days from 13 MPa to (17-18) MPa for (natural and in
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Iraqi conventional gasoline characterized by its low octane number not exceed 82 and high lead and sulfur content. In this paper tri-component or ternary, blends of gasoline, ethanol, and methanol presented as an alternative fuel for Iraqi conventional gasoline. The study conducted by using GEM blend that equals E85 blend in octane rating. The used GEM selected from Turner, 2010 collection. G37 E20 M43 (37% gasoline + 20% ethanol+ 43% methanol) was chosen as GEM in present study. This blend used in multi-cylinder Mercedes engine, and the engine performance, and emitted emissions compared with that produced by a gasoline engine.
The results show that this blend can formulate with available Iraqi pro
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