: 1-10
Received: October 10, 2019
Accepted: November 20, 2019
Lviv Polytechnic National University, Lviv, Ukraine
Lviv Polytechnic National University, Lviv, Ukraine
Lviv Polytechnic National University, Department of Automated Control Systems

It is shown that energy ef­fi­ci­ency impro­ve­ment of the re­gi­on's eco­nomy is re­ali­zed thro­ugh the use of in­for­ma­ti­on-analyti­cal me­ans of sup­por­ting energy ef­fi­ci­ency ma­na­ge­ment, which are ba­sed on in­tel­lec­tu­al in­for­ma­ti­on, Web and te­le­com­mu­ni­ca­ti­on techno­lo­gi­es. Archi­tec­tu­re of an in­for­ma­ti­on-analyti­cal system (IAS) for ma­na­ging the energy ef­fi­ci­ency of the re­gi­on's eco­nomy has be­en de­ve­lo­ped ba­sed on the prin­cip­les of mo­du­la­rity, open­ness, com­pa­ti­bi­lity and use of a set of ba­sic de­sign so­lu­ti­ons. IAS pro­vi­des col­lec­ti­on, pro­ces­sing and vis­ua­li­za­ti­on of energy da­ta, mo­de­ling, fo­re­cas­ting of energy ef­fi­ci­ency ma­na­ge­ment pro­ces­ses and sup­port of energy ef­fi­ci­ency ma­na­ge­ment de­ci­si­ons for re­gi­onal eco­no­mic. The cre­ati­on of a uni­fi­ed in­for­ma­ti­on spa­ce with re­li­ab­le, comple­te and ti­mely in­for­ma­ti­on that is used to ge­ne­ra­te ef­fec­ti­ve ma­na­ge­ment de­ci­si­ons is en­su­red. On the ba­sis of the In­ter­net of Things con­cept de­ve­lo­ped da­ta col­lec­tors that are the spa­ti­ally distri­bu­ted small in­tel­li­gent sen­sors lin­ked to a clo­ud ser­ver. It is shown that it is ex­pe­di­ent to de­ve­lop the com­po­nents of the geoin­for­ma­ti­on system for the IACEA re­gi­on eco­nomy using Go­og­le Clo­ud Ser­vi­ces and the spe­ci­ali­zed Go­og­le Maps API, which will pro­vi­de promptly cre­ati­on, mo­di­fi­ca­ti­on and incre­ase of in­for­ma­ti­on ca­pa­bi­li­ti­es. It is ar­gu­ed that the ad­di­ti­onal in­vol­ve­ment of prog­ram­ming to­ols, inclu­ding Ja­vaScript, using the Go­og­le Maps API pro­vi­des the op­por­tu­nity to de­ve­lop a geoin­for­ma­ti­on system for the IAS for sup­por­ting energy ef­fi­ci­ency ma­na­ge­ment of re­gi­onal eco­nomy, ta­king in­to ac­co­unt ad­di­ti­onal spe­ci­fic fu­tu­re req­ui­re­ments of the thesis system. It is pro­po­sed cre­ati­on of the IAS for sup­por­ting energy ef­fi­ci­ency ma­na­ge­ment on the ba­sis of da­ta­ba­ses and da­ta wa­re­hou­ses, spe­ci­ali­zed pub­licly ava­ilab­le GIS to­ols for vis­ua­li­za­ti­on and analysis of energy con­sumpti­on and energy ef­fi­ci­ency da­ta, which will en­su­re the fe­asi­bi­lity and ef­fi­ci­ency of ge­ne­ra­ted ma­na­ge­ment de­ci­si­ons. It is shown that the vis­ua­li­za­ti­on of energy da­ta and pro­ces­sing re­sults in the most hu­man-re­adab­le form with pre­ci­se lo­ca­ti­ons of the ma­na­ge­ment fa­ci­li­ti­es pro­vi­des ef­fec­ti­ve sup­port for ma­na­ge­ment de­ci­si­ons.

[1]     Ber­toc­co, M., Cap­pel­laz­zo, S., Flam­mi­ni, A., & Par­vis, M. (2002). A mul­ti-la­yer archi­tec­tu­re for distri­bu­ted da­ta ac­qui­si­ti­on. Pro­ce­edings of the 19th IEEE Instru­men­ta­ti­on and Me­asu­re­ment Techno­logy Con­fe­ren­ce, 2, 1261-1264.
[2]     Big Da­ta Imple­men­ta­ti­on Vs. (2019). Da­ta Wa­re­hou­sing. Ret­ri­eved from:
[3]     Bulls, N. (2018). Big Da­ta Vis­ua­li­za­ti­on To­ols. Encyclo­pe­dia of Big Da­ta Techno­lo­gi­es. Sprin­ger. Ret­ri­eved from:
[4]     Chiu, Yu. Hsi­en, et al. (2014). En­terpri­se re­so­ur­ce plan­ning. New-York, 268 p.
[5]     Da­ta Vis­ua­li­za­ti­on. (2015). Da­ta Vis­ua­li­za­ti­on for Hu­man Per­cep­ti­on. The In­te­rac­ti­on De­sign Fo­un­da­ti­on. Ret­ri­eved from:
[6]     Da­ta Wa­re­hou­se De­sign. (2019). Ret­ri­eved from:
[7]     Da­ta Wa­re­hou­sing. (2019). Big Da­ta and Its Im­pact on Da­ta Wa­re­hou­sing. Ret­ri­eved from:
[8]     Di­aman­ta­ras, K. I., & Kung, S. Y. (1996). Prin­ci­pal Com­po­nent Neu­ral Net­works: The­ory and Appli­ca­ti­ons. Wi­ley, 270 p.
[9]     Fri­ed­man, V. (2008). Da­ta Vis­ua­li­za­ti­on and In­fog­rap­hics. in: Grap­hics, Mon­day Inspi­ra­ti­on, Jan­uary 14th, 2008. Ret­ri­eved from:
[10]  Kar­pa, D. M., Tsmots, I. G., & Teslyuk, V. M. (2019). De­ci­si­on sup­port to­ols for pri­ori­ti­zing energy-sa­ving pro­jects. Sci­en­ti­fic Bul­le­tin of UN­FU, 29(2), 135-140. [In Uk­ra­ini­an].
[11]  Lambda Archi­tec­tu­re. (2019). Ret­ri­eved from:
[12]  Lengler, Ralph, & Eppler, Mar­tin. J. (2019). Pe­ri­odic Tab­le of Vis­ua­li­za­ti­on Met­hods. Ret­ri­eved from:
[13]  Me­di­kovsky, M. O., Tsmots, I. G., & Po­dolsky, M. R. (2013). Substan­ti­ati­on of the prin­cip­les of construc­ti­on and de­ve­lop­ment of the ge­ne­ra­li­zed struc­tu­re of the in­for­ma­ti­on-analyti­cal system for es­ti­ma­ti­on, fo­re­cas­ting and ma­na­ge­ment of energy ef­fi­ci­ency of the re­gi­on's eco­nomy. (Ser. Com­pu­ter sci­en­ces and in­for­ma­ti­on techno­lo­gi­es). Bul­le­tin of NU "Lviv Polytechnic", 751, 40-51. Lviv. [In Uk­ra­ini­an].
[14]  Medykovsky, M. O., Tkac­hen­ko, R. O., Tsmots, I. G., Tsym­bal, Yu. V., Do­ros­hen­ko, A. V., & Sko­rok­ho­da, O. V. (2015). In­tel­lec­tu­al com­po­nents of in­teg­ra­ted au­to­ma­ted control systems. Lviv: Lviv Polytechnic Pub­lis­hing Hou­se, 280 p. [In Uk­ra­ini­an].
[15]  Medykovskyi, M. O., Tsmots, I. G., & Sko­rok­ho­da, О. В. (2014). Spectrum neu­ral net­work filtra­ti­on techno­logy for impro­ving the fo­re­cast ac­cu­racy of dyna­mic pro­ces­ses in eco­no­mics. Ac­tu­al Prob­lems of Eco­no­mics, 12(162), 410-416.
[16]  Medykovskyi, M. O., Tsmots, I. G., & Tsymbal, Yu. V. (2013). In­tel­li­gent da­ta pro­ces­sing to­ols in energy ef­fi­ci­ency ma­na­ge­ment systems for re­gi­onal eco­nomy. Ac­tu­al Prob­lems of Eco­no­mics, 12(150), 271-277.
[17]  Medykovskyi, M. O., Tsmots, I. G., Sko­rok­ho­da, О. В., & Teslyuk, T. V. (2016). De­sign of In­tel­li­gent Com­po­nent of Hi­erarchi­cal Control System. Econ­techmod: An In­ter­na­ti­onal Qu­ar­terly Jo­ur­nal, 5(2.3), 3-10.
[18]  Medykovskyi, M. O., Tsmots, I. H., & Tsymbal, Yu. V. (2016). In­for­ma­ti­on analyti­cal system for energy ef­fi­ci­ency ma­na­ge­ment at en­terpri­ses in the city of Lviv (Uk­ra­ine). Ac­tu­al Prob­lems of Eco­no­mics, 1(175), 379-384.
[19]  O'Le­ary, D. E. (2000). En­terpri­se re­so­ur­ce plan­ning systems: systems, li­fe cycle, electro­nic com­mer­ce, and risk. Cambrid­ge Uni­ver­sity Press.
[20]  Teslyuk, T., Tsmots, I., Teslyuk, V., Medykovskyi, M., & Opot­yak, Y. (2017). Archi­tec­tu­re of the ma­na­ge­ment system of energy ef­fi­ci­ency of techno­lo­gi­cal pro­ces­ses in the en­terpri­se. Pro­ce­edings of the 12th In­ter­na­ti­onal Sci­en­ti­fic and Techni­cal Con­fe­ren­ce, Sep­tem­ber 5-8, 2017, Lviv, (pp. 429-433).
[21]  Teslyuk, T., Tsmots, I., Teslyuk, V., Medykovskyy, M., & Opot­yak, Y. (2018). Archi­tec­tu­re and Mo­dels for System-Le­vel Com­pu­ter-Aided De­sign of the Energy Ef­fi­ci­ency Ma­na­ge­ment System of Techno­lo­gi­cal Pro­ces­ses at the En­terpri­se. Au­to­ma­ti­on 2017. Ad­van­ces in In­tel­li­gent Systems and Com­pu­ting: In­ter­na­ti­onal Con­fe­ren­ce, 689, 538-557. Sprin­ger.
[22]  Tsmot, I. G., Teslyuk, T. V., Opot­yak, Yu. V., & Teslyuk, V. M. (2017). Archi­tec­tu­re of a Mul­ti­le­vel Energy Ef­fi­ci­ency Ma­na­ge­ment System in the Re­gi­on. (Ser. Com­pu­ter Sci­en­ce and In­for­ma­ti­on Techno­lo­gi­es). Bul­le­tin of the Na­ti­onal Techni­cal Uni­ver­sity of Lviv Polytechnic, 864, 201-209. Lviv. [In Uk­ra­ini­an].
[23]  Tsmots, I. G., & Ro­man, V. I. (2019). Impro­ving the met­hod of grou­ping energy da­ta in the system of mul­ti­le­vel energy ef­fi­ci­ency ma­na­ge­ment of the re­gi­on's eco­nomy. Sci­en­ti­fic Bul­le­tin of UN­FU, 29(1), 116-120. [In Uk­ra­ini­an].
[24]  Tsmots, I. G., Sko­rok­ho­da, O. V., & Ro­man, V. I. (2016). Da­ta re­po­si­to­ri­es of mul­ti­le­vel energy ef­fi­ci­ency ma­na­ge­ment systems. Mo­de­ling and in­for­ma­ti­on techno­lo­gi­es, 77, 192-197. Insti­tu­te of Mo­de­ling Prob­lems in Energy. [In Uk­ra­ini­an].
[25]  Tsmots, I. G., Tsymbal, Yu. V., & Tsmots, O. I. (2012). Early war­ning systems for en­terpri­ses using neu­ral net­works to­ols. Ac­tu­al Prob­lems of Eco­no­mics, 10(136), 283-291.
[26]  Tsymbal, Yu., & Tkac­hen­ko, R. (2016). A Di­gi­tal Wa­ter­mar­king Sche­me Ba­sed on Au­to­as­so­ci­ati­ve Neu­ral Net­works of the Ge­omet­ric Transfor­ma­ti­ons Mo­del. Pro­ce­edings of the 2016 IEEE First In­ter­na­ti­onal Con­fe­ren­ce on Da­ta Stre­am Mi­ning & Pro­ces­sing, (pp. 231-234).