Internet of Things for Smart Agriculture monitoring and prediction system

Internet of Things for Smart Agriculture monitoring and prediction system

Differences in the Sub-seasonal Predictability of Extreme Stratospheric Events

Extreme stratospheric events such as sudden stratospheric warming and strong vortex events associated with an anomalously weak or strong polar vortex can have downward impacts on surface weather that can last for several weeks to months. Hence, successful predictions of these stratospheric events would be beneficial for extended range weather prediction. However, the predictability limit of extreme stratospheric events is most often limited to around 2 weeks or less. The predictability also strongly differs between events, and between event types. The reasons for the observed differences in the predictability, however, are not resolved. To better understand the predictability differences between events, we expand the definitions of extreme stratospheric events to wind deceleration and acceleration events, and conduct a systematic comparison of predictability between event types in the European Centre for Medium-Range Weather Forecasts (ECMWF) prediction system for the sub-seasonal predictions. We find that wind deceleration and acceleration events follow the same predictability behaviour, that is, events of stronger magnitude are less predictable in a close to linear relationship, to the same extent for both types of events. There are however deviations from this linear behaviour for very extreme events. The difficulties of the prediction system in predicting extremely strong anomalies can be traced to a poor predictability of extreme wave activity pulses in the lower stratosphere, which impacts the prediction of deceleration events, and interestingly, also acceleration events. Improvements in the understanding of the wave amplification that is associated with extremely strong wave activity pulses and accurately representing these processes in the model is expected to enhance the predictability of stratospheric extreme events and, by extension, their impacts on surface weather and climate.

A Whole Process Cost Prediction System for Construction Projects Based on Improved Support Vector Machines

The current project cost system requires high data scale, small amount of data and large prediction deviation. In order to improve the prediction accuracy of the whole process cost of construction project, this paper designs a whole process project cost prediction system based on improved support vector machine. In the hardware part of the system, the control core adopts arm controller S3C6410 and introduces 4G communication module to analyze the actual engineering data with the support of hardware. In the software part, the whole process cost prediction index system of the construction project is established, the index is reduced by the principal component method, and the support vector machine is improved by particle swarm optimization algorithm to realize the whole process cost prediction of the project. The system function test results show that the average prediction deviation of the designed system is 4.11%, the average prediction deviation of the cost prediction system is 3.05%, and the average prediction deviation of the system is 1.57%.

Outcomes and challenges of Forecast Demonstration Project (FDP) on landfalling cyclones over the Bay of Bengal

Cakxky dh [kkM+h esa m".kdfVca/kh; rwQkuksa ds ekxZ vkSj mudh rhozrk ds iwokZuqeku rduhd esa lq/kkj ykus ds fy, iwokZuqeku fun’kZu ifj;kstuk ¼,Q-Mh-ih-½ uked ,d dk;ZØe rS;kj fd;k x;k gSA ,Q-Mh-ih- dk;ZØe dk mÌs’;] ftu {ks=ksa ls vk¡dM+s vO;ofLFkr :i ls izkIr gksrs gSa ogk¡ muds loaf/kZr izs{k.kksa ds lkFk gh lkFk mRrjh fgUn egklkxj esa pØokrksa ds mRiUu gksus] muds rhoz gksus vkSj mudh xfr dk vkdyu djus ds fy, fofHkUu l[;kRed ekSle iwokZuqeku ¼,u- MCY;w- ih-½ fun’kksZ dh {kerk dk izn’kZu djuk rFkk fo’ks"k :i ls caxky dh [kkM+h ls lacaf/kr ogha mlh LFkku ij fy, x, ekiksa ds vk/kkj ij fun’kksZ esa lq/kkj djuk gSA ,Q-Mh-ih- dk;ZØe rhu pj.kksa esa fu/kkfjr fd;k x;k gS uker% ¼i½ izh&ikbyV pj.k ¼15 vDrwcj ls 30 uoacj 2008] 2009½] ¼ii½ ikbyV pj.k ¼15 vDrwcj ls 30 uoacj 2010&2012½ rFkk ¼iii½ vafre pj.k ¼15 vDrwcj ls 30 uoacj 2013&2014½A Hkkjr] fdjk, ds gokbZ tgkt vkSj MªkWilkSansa iz;ksxksa ls 15 vDrwcj ls 30 uoacj 2013&2014 ds nkSjku caxky dh [kkM+h esa cuus okys pØokrksa dk gokbZ tgkt ds tfj, irk yxkus dh ;kstuk cuk jgk gSA bl mÌs’; ds iwfrZ ds fy, ¼i½ izs{k.kkRed mUu;u ¼ii½ pØokr fo’ys"k.k vkSj iwokZuqeku iz.kkyh dk vk/kqfudhdj.k ¼iii½ pØokr fo’ys"k.k vkSj iwokZuqeku izfØ;k ¼iv½ psrkouh mRiknksa dks rS;kj djuk] mudk izLrqrhdj.k rFkk izlj.k ¼v½ fo’oluh;rk mik; vkSj {kerk fuekZ.k ij izkFkfedrk ds vk/kkj ij dk;Z fd, x,A pØokr ds izs{k.k] fo’ys"k.k vkSj iwokZuqeku esa lq/kkj ykus ds fy, fofHkUu dk;Z iz.kkfy;k¡ viukbZ xbZaA o"kZ 2008&11 ds nkSjku ,Q-Mh-ih- vfHk;ku ds izh&ikbyV vkSj ikbyV pj.kksa esa la;qDr izs{k.kkRed] lapkjkRed vkSj ,u-MCY;w-ih- xfrfof/k;ksa esa vusd jk"Vªh; laLFkkuksa us Hkkx fy;kA ,Q-Mh-ih- ds igys vkSj mlds ckn dh izs{k.kkRed iz.kkfy;ksa dh rqyuk ls {ks= esa jsMkj] Lopkfyr ekSle dsUnz ¼,- MCY;w-,l-½] mPp iou xfr fjdkWMjksa esa egRoiw.kZ lq/kkj dk irk pyk gSA bl lq/kkj ls ekWuhVju vkSj iwokZuqeku esa gksus okyh =qfV;ksa esa deh vkbZ gSA th- ,Q- ,l- MCY;w vkj- ,Q] ,p- MCY;w- vkj- ,Q- vkSj vlsEcy iwokZuqeku iz.kkyh ¼bZ- ih- ,l-½ ds vkjaHk gksus ls ,u- MCY;w- ih- funsZ’kksa ds dk;Z fu"iknu esa o`f) gqbZ gSA bl 'kks/k i= esa bl ifj;kstuk dh miyfC/k;ksa ds egRoiw.kZ y{k.kksa lfgr leL;kvksa vkSj laHkkoukvksa dks izLrqr fd;k x;k gS rFkk mudh foospuk dh xbZ gSA pØokrksa dk gokbZ tgkt }kjk irk yxkus ds fy, ckj&ckj fd, x, iz;klksa ds ckotwn ;g dk;Z vHkh laHko ugha gks ldk gSA o"kZ 2013&14 ds nkSjku Hkkoh vfHk;ku ds le; ;g ,d eq[; pqukSrh gksxhA A programme has been evolved for improvement in prediction of track and intensity of tropical cyclones over the Bay of Bengal resulting in the Forecast Demonstration Project (FDP). FDP programme is aimed to demonstrate the ability of various Numerical Weather Prediction (NWP) models to assess the genesis, intensification and movement of cyclones over the north Indian ocean with enhanced observations over the data sparse region and to incorporate modification into the models which could be specific to the Bay of Bengal based on the in-situ measurements. FDP Programme is scheduled in three phases, viz., (i) Pre-pilot phase (15 Oct - 30 Nov 2008, 2009, (ii) Pilot phase (15 Oct - 30 Nov, 2010-2012) and (iii) Final phase (15 Oct - 30 Nov, 2013-14). India is planning to take up aircraft probing of cyclones over the Bay of Bengal during 15 Oct - 30 Nov, 2013-14 with hired aircraft and dropsonde experiments. To accomplish the above objective, the initiative was carried out with priorities on (i) observational upgradation, (ii) modernisation of cyclone analysis and prediction system, (iii) cyclone analysis and forecasting procedure, (iv) warning products generation, presentation & dissemination, (v) confidence building measures and capacity building. Various strategies were adopted for improvement of observation, analysis and prediction of cyclone. Several national institutions participated for joint observational, communicational & NWP activities during the pre-pilot and pilot phases of FDP campaign during 2008-11. The comparison of observational systems before and after FDP indicates a significant improvement in terms of Radar, Automatic Weather Station (AWS), high wind speed recorders over the region. It has resulted in reduction in monitoring and forecasting errors. The performance of NWP models have increased along with the introduction of NWP platforms like IMD GFS, WRF, HWRF and ensemble prediction system (EPS). Salient features of achievements along with the problems and prospects of this project are presented and discussed in this paper. With repeated attempts, the aircraft probing of cyclones could not be possible till now. It is a major challenge for the future campaign during 2013-14.