Energy Saving of an Intelligent Lighting System with Presence Management using IC Cards

Energy Saving of an Intelligent Lighting System with Presence Management using IC Cards

Mitsunori MIKI^*, Hisanori IKEGAMI^**, Shohei MATSUSHITA^** , Yohei AZUMA^** , Keigo MACHIDA^** , Shohei FUJIMOTO^** , Yuki KURANO^** and Hiroto AIDA^*

(Received January 20, 2014)

The Intelligent Lighting System can provide individual illuminance environment each worker desires, and it also can save energy. In addition, when many users leave their desk, this system turn off the unnecessary lighting. As a result, it can achieve high energy saving. Traditionally, worker enter presence information using Web UI. However, in validation experiments in an office, as only some worker enter presence information, unnecessary lights keep lighting. As improvement of entry presence information, we proposed the Intelligent Lighting System that incorporates the input of presence information using IC card. When worker occupy the seat, they set their IC card on IC card reader. Then, this system provides the necessary illuminance at the requested location. On the other hand, when worker leave their desks, they remove their IC card from IC card reader.As a result of verification, it was confirmed that this system achieves the improvement of entry presence information, and shows the higher energy saving compared with traditional system.

Key words : intelligent lighting systemɼoffice Ωʔϫʔυ: ஌తর໌γεςϜɼΦϑΟε

IC ΧʔυʹΑΔࡏ੮؅ཧΛಋೖͨ͠

஌తর໌γεςϜͷলΤωϧΪʔੑೳ

ࡾ ໦ ޫ ൣ, ஑ ্ ٱ య, দ Լ ণ ฏ, ౦ ཅ ฏ, ொ ా ܒ ޛ, ౻ ຊ ঵ ฏ, ଂ ໺ ༟ ݾ, ؒ ത ਓ

1. ং࿦

஍ٿԹஆԽ๷ࢭ͕ੈքͷॏཁͳ՝୊ͱͯ͠औΓ্͛

ΒΕɼզ͕ࠃʹ͓͍ͯ΋ΤωϧΪʔ࢖༻ྔΛେ෯ʹ࡟

ݮ͢Δ͜ͱ͸ɼۓٸͷ՝୊ͱͯ͠औΓ૊·Ε͍ͯΔɽ ಛʹɼۀ຿༻ϏϧͷফඅΤωϧΪʔ͸೥ʑ૿Ճ͓ͯ͠

Γɼ͜ͷ෦໳ʹ͓͚ΔলΤωϧΪʔ͸ɼࠃશମʹͱͬ

ͯΤωϧΪʔͷେ͖ͳ࡟ݮʹͭͳ͕ΔɽΦϑΟεϏϧ ʹ͓͍ͯ͸ɼর໌ʹ༻͍Δిྗίετ͕Ϗϧશମͷ໿

20 %Λ઎Ί͓ͯΓɼর໌ʹର͢ΔলΤωϧΪʔରࡦ͸

ॏཁͳ՝୊Ͱ͋Δɽ

·ͨɼΦϑΟε؀ڥ͕ΦϑΟεϫʔΧͷੜ࢈ੑʹٴ

΅͢Өڹʹؔ͢Δݚڀ͕޿͘ߦͳΘΕ͓ͯΓɼΦϑΟ

* Department of Science and Engineering, Doshisha University, Kyoto

Telephone:+81-774-65-6930, Fax:+81-774-65-6716, E-mail:[email protected]

** Graduate School of Science and Engineering, Doshisha University, Kyoto

Telephone:+81-774-65-6930, Fax:+81-774-65-6716, E-mail:[email protected]

ε؀ڥΛվળ͢Δ͜ͱͰɼϫʔΧͷੜ࢈ੑ͕޲্͢Δ

͜ͱ͕ใࠂ͞Ε͍ͯΔ^{1, 2)}ɽಛʹɼΦϑΟε؀ڥͷ͏

ͪর໌؀ڥʹண໨ͨ͠ݚڀͰ͸ɼࣥ຿ʹ࠷దͳ໌Δ͞

ʢর౓ʣΛݸਓ͝ͱʹఏڙ͢Δ͜ͱ͕ΦϑΟε؀ڥͷ վળʹ༗ޮͰ͋Δ͜ͱ͕ݴٴ͞Ε͍ͯΔ³⁾ɽ͜ͷΑ͏

ʹࣥ຿ʹ࠷దͳ໌Δ͞Λݸਓ͝ͱʹఏڙ͢Δ͜ͱ͸ɼ λεΫর໌Λ༻͍Δ͜ͱͰ༰қʹ࣮ݱՄೳͰ͋Δɽ͠

͔͠ͳ͕ΒɼݱࡏͷΦϑΟεͰ͸ɼϑϩΞʹۉҰͳ໌

Δ͞Λఏڙ͢ΔఱҪর໌͕ҰൠతͰ͋ΓɼλεΫর໌

Λ࠾༻͢Δ͜ͱ͸༰қͰ͸ͳ͍ɽ͜ͷҝɼطଘͷఱҪ র໌Λ༻͍ͯɼݸਓ͝ͱʹ࠷దͳ໌Δ͞Λఏڙ͢Δর

໌γεςϜ͕ඞཁͱͳΔɽ

͜ͷΑ͏ͳ՝୊Λղܾ͢Δর໌γεςϜͱͯ͠ɼච

ऀΒ͸஌తর໌γεςϜͱ໊෇͚ͨর໌γεςϜͷݚ ڀ։ൃʹऔΓ૊ΜͰ͍Δ^{4, 5)}ɽ஌తর໌γεςϜ͸ɼ೚

ҙͷ৔ॴʹ೚ҙͷ໌Δ͞Λఏڙ͢Δ͜ͱͰɼϫʔΧͷ

஌తੜ࢈ੑͷ޲্΍ফඅిྗྔͷ࡟ݮΛ࣮ݱ͢Δγε ςϜͰ͋Δɽ஌తর໌γεςϜ͸ɼϚΠΫϩϓϩηο α͕૊Έࠐ·Εͨෳ਺ͷௐޫՄೳͳর໌ث۩ɼෳ਺ͷ র౓ηϯαɼ͓ΑͼిྗܭΛɼωοτϫʔΫʹ઀ଓ͢

Δ͜ͱͰߏ੒͞ΕΔɽ֤র໌͸ωοτϫʔΫʹྲྀΕΔ র౓৘ใ͓Αͼిྗྔʹؔ͢Δ৘ใΛجʹɼࣗ཯෼ࢄ

࠷దԽΞϧΰϦζϜΛ༻͍ͯɼ໨ඪর౓Λ࣮ݱͭͭ͠

௿ফඅిྗͱͳΔ࠷దͳ఺౮ύλʔϯΛ࣮ݱ͢Δɽ

͜Ε·Ͱɼ೚ҙͷ৔ॴʹ೚ҙͷ໌Δ͞Λఏڙ͢Δ͜

ͱͰɼߴ͍লΤωϧΪʔੑΛ࣮ݱ͢Δ஌తর໌γες Ϝͷ༗ޮੑ͕࣮ݧࣨʹ͓͍ͯ֬ೝ͞Ε͍ͯͨ⁵⁾ɽ࣮༻

ԽʹΉ͚࣮ͯΦϑΟεʹಋೖͨ͠ͱ͜ΖɼҰ෦ͷϢʔ βͷΈ͕ࡏ੮ɾ཭੮৘ใͷೖྗΛߦ͍ͬͯΔͱ͍͏ঢ় گͰ͋Δ͜ͱ͕Θ͔ͬͨɽ࣮ࡍ͸Ϣʔβ͕ෆࡏͰ͋Δ ʹ΋͔͔ΘΒͣɼෆඞཁͳর໌͕఺౮͍ͯ͠ΔͨΊʹɼ

஌తর໌γεςϜͷলΤωϧΪʔੑ͕௿Լ͓ͯ͠Γɼ ԿΒ͔ͷํ๏Ͱࡏ੮཭੮ηϯγϯάΛߦ͏ඞཁ͕͋ͬ

ͨɽຊߘͰ͸ɼΦϑΟεͷࣾһূʹଟ͘࢖༻͞ΕΔඇ

઀৮ICΧʔυΛ༻͍ͯɼࡏ੮ɾ཭੮৘ใͷೖྗΛ࣮

ݱ͢Δ஌తর໌γεςϜΛఏҊ͢ΔɽICΧʔυʹΑ Δࡏ཭੮ݕ஌Λߦ͏͜ͱͰɼWebUIΛ༻͍Δࡏ཭੮

൑ఆΛ࠾༻ͨ͠஌తর໌γεςϜΑΓ΋লΤωϧΪʔ

Fig. 1. Configuration of the intelligent lighting sys- tem.

ੑೳ͕޲্͢Δ͜ͱΛࣔ͢ɽ

2. ஌తর໌γεςϜ 2.1 ஌తর໌γεςϜͷ֓ཁ

஌తর໌γεςϜ͸ɼ೚ҙͷ৔ॴʹϢʔβ͕ཁٻ͢

Δ໌Δ͞ʢর౓ʣΛఏڙ͢Δর໌੍ޚγεςϜͰ͋Δɽ ௐޫ͕Մೳͳෳ਺ͷর໌ػثͱෳ਺ͷর౓ηϯαɼ͓

ΑͼిྗܭΛҰͭͷωοτϫʔΫʹ઀ଓ͢Δ͜ͱͰߏ

੒͞ΕΔɽFig. 1ʹ஌తর໌γεςϜͷߏ੒Λࣔ͢ɽ

֤র໌ػثʹͦΕͧΕ੍ޚ૷ஔ͕౥ࡌ͞Ε͓ͯΓɼ

੍ޚ૷ஔ͕֤র౓ηϯα͔Βͷর౓৘ใɼ͓Αͼిྗ

ܭ͔Βফඅిྗ৘ใΛऔಘͰ͖Δɽ஌తর໌γεςϜ

͸ɼཁٻর౓Λຬͨ͢࠷దͳ఺౮ύλʔϯΛ࣮ݱ͢Δ

ͨΊʹɼ͜ͷ໰୊Λ࠷దԽ໰୊ͱͯ͠ఆٛ͢Δɽর౓

৘ใ͓Αͼফඅిྗྔ৘ใΛϑΟʔυόοΫ͠ͳ͕Βɼ ਐԽతΞϧΰϦζϜʹجͮ͘࠷దԽख๏Λ༻͍ͯɼ੍

ޚ૷ஔ͕র໌ͷ໌Δ͞ʢޫ౓ʣΛ੍ޚ͢Δɽ͜ΕʹΑ ΓɼϢʔβ͕ཁٻ͢Δ໌Δ͞Λ࣮ݱ͠ɼෆඞཁͳ໌Δ

͞Λ཈͑Δ͜ͱͰɼফඅిྗྔͷ࡟ݮΛਤΔɽ

2.2 ໨తؔ਺

஌తর໌γεςϜ͸ɼর౓ηϯαΛઃஔͨ͠৔ॴͷ র౓Λ໨ඪͱ͢Δর౓Ҏ্ʹ͠ɼর໌͕࢖༻͢Δిྗ

ྔΛ࠷খʹͳΔΑ͏ʹর໌ͷޫ౓Λ֤র໌͕ࣗ཯తʹ ٻΊΔɽ͜ΕΒΛ໨తؔ਺ͱͯ͠ఆࣜԽ͢Δඞཁ͕͋

Δɽ໨తؔ਺Λeq.(1)ʹࣔ͢ɽ

fi = P+w×

n

j=1

gij (1)

gij =

0 (Icj−Itj)≥0

Rij×(Icj−Itj)² (Icj−Itj)<0

Rij =

rij rij≥T

0 rij< T

iɿর໌ID,jɿηϯαID,wɿॏΈ[W/lx²],Pɿফඅ

ిྗྔ[W], Icɿݱࡏͷর౓[lx]

Itɿ໨ඪর౓[lx],Tɿᮢ஋,rijɿর໌iʹର͢Δর౓

ηϯαjͷճؼ܎਺

eq.(1)ʹࣔ͢Α͏ʹ໨తؔ਺fi͸ɼফඅిྗྔPɼ

͓Αͼর౓ηϯαjͷ໨ඪর౓ʹؔ͢Δ੍໿Λද͢ϖ φϧςΟ߲gij͔ΒͳΔɽϖφϧςΟ߲gijʹ͸ɼݱࡏ র౓ͱ໨ඪর౓ͱͷࠩΛ༻͍͓ͯΓɼ໨ඪর౓͕ຬͨ

͞Εͳ͍৔߹ʹͷΈϖφϧςΟΛֻ͚͍ͯΔɽ͜Εʹ ΑΓɼ໨ඪর౓ͱݱࡏর౓͕཭ΕΔ΄Ͳɼ໨తؔ਺஋

͕େ͖͘૿Ճ͢Δɽ·ͨɼ֤র໌ͷޫ౓มԽྔͱর౓

ηϯαͰଌఆ͞Εͨর౓มԽྔ͔Βࢉग़ͨ͠ճؼ܎਺

͕͋Δఔ౓খ͍͞ʢᮢ஋Tະຬʣ৔߹ʹ͸0Λ৐ࢉ͢

Δɽͭ·Γɼճؼ܎਺ͷ௿͍র౓ηϯα͕໨ඪΛຬͨ

͞ͳ͍৔߹ʹ͸ɼ໨తؔ਺஋͕૿Ճ͠ͳ͍ɽΏ͑ʹɼ ճؼ܎਺ͷߴ͍ɼ͢ͳΘͪͦͷর໌͕ӨڹΛ༩͑Δর

౓ηϯαʹͷΈ࠷దԽͷର৅ΛߜΔ͜ͱ͕Ͱ͖Δɽ͜

ΕʹΑΓɼ໨ඪর౓Λຬͨ͢ਫ਼౓͕޲্͢Δɽ

·ͨɼgijʹ͸ॏΈwΛ৐ࢉ͠ɼ͜ͷwͷ஋ʹΑΓɼ

໨ඪর౓ͷ੍໿৚݅·ͨ͸ɼফඅిྗྔͷ࠷খԽͷͲ

ͪΒΛ༏ઌ͢Δ͔Λܾఆ͢Δɽ 2.3 র໌੍ޚΞϧΰϦζϜ

ஶॻΒ͸র໌੍ޚΞϧΰϦζϜͱͯ͠ɼ֬཰తࢁొ

Γ๏ʢStochastic Hill ClimbingɿSHCʣΛجʹর໌੍ޚ

༻ʹճؼ܎਺Λ༻͍ͨదԠతۙ๣ΞϧΰϦζϜʢAdap- tive Neighborhood Algorithm using Regression Co- efficientɿANA/RCʣ⁶⁾ΛఏҊͨ͠ɽANA/RCͰ͸ɼ

֤র໌ͷޫ౓มԽྔͱর౓ηϯαͰଌఆ͞Εͨর౓ม Խྔ͔Βࢉग़ͨ͠ճؼ܎਺Λ༻͍ͯɼর໌ͷޫ౓͕֤

র౓ηϯαͷর౓ʹӨڹΛ༩͑Δ౓߹͍ʢҎԼɼӨڹ

౓ͱ͢ΔʣΛֶश͠ɼঢ়گʹԠͨۙ͡๣ઃܭʹجͮ͘

ޫ౓มԽΛͤ͞Δ͜ͱͰɼ࠷దͳޫ౓΁ͱૉૣ͘มԽ

ͤ͞Δ͜ͱ͕Ͱ͖Δɽճؼ܎਺Λ༻͍ͨదԠతۙ๣Ξ

ϧΰϦζϜͷϑϩʔνϟʔτΛFig. 2ʹࣔ͠ɼҎԼʹ ຊΞϧΰϦζϜͷྲྀΕΛઆ໌͢Δɽ

1. ॳظޫ౓Ͱ఺౮͢Δ

2. ֤র౓ηϯαͷηϯα৘ใʢηϯαIDɼݱࡏͷ র౓ɼ໨ඪর౓ʣɼ͓ΑͼిྗܭͷফඅిྗྔΛ औಘ͠ɼͦΕΒͷ৘ใΛ༻͍ͯ໨తؔ਺஋Λܭࢉ

͢Δ

3. ηϯα৘ใɼճؼ܎਺ʹج͖ͮద੾ͳۙ๣Λܾఆ

͢Δʢۙ๣ͱ͸࣍ޫ౓Λੜ੒͢Δҝʹ༻͍Δൣғ Ͱ͋Δɽ2.5અʹͯৄ͘͠ड़΂Δɽʣ

4. ߲໨3Ͱܾఆͨۙ͠๣಺ʹ࣍ޫ౓ΛϥϯμϜʹੜ

੒͠ɼর໌͸ͦͷޫ౓Ͱ఺౮͢Δ

5. ࠶ͼ֤র౓ηϯαͷηϯα৘ใɼ͓Αͼిྗܭͷ ফඅిྗྔΛऔಘ͠ɼͦΕΒͷ৘ใΛ༻͍ͯ࣍ޫ

౓Ͱ఺౮ͨ͠ঢ়ଶͰͷ໨తؔ਺஋Λܭࢉ͢Δ 6. র໌ͷޫ౓มԽྔͱর౓ηϯαͷর౓มԽྔΛ༻

͍ͯճؼ܎਺Λܭࢉ͢Δ

7. ໨తؔ਺஋͕վྑͨ͠৔߹ɼͦͷޫ౓Λ֬ఆ͢Δ 8. ߲໨5Ͱ໨తؔ਺஋͕վѱͨ͠৔߹ɼલͷޫ౓Ͱ

࠶౓఺౮͢Δ

9. র໌͕࠷খ఺౮ޫ౓Ͱ͋ΓɼӨڹ͕͋Δ͢΂ͯͷ র౓ηϯαʹ໨ඪর౓͕ཁٻ͞Ε͍ͯͳ͍৔߹ɼ ফ౮Λߦ͍ɼ߲໨2΁໭Δ

10. র໌͕ফ౮͓ͯ͠Γɼফ౮࣌ʹӨڹ͕͋ͬͨর౓

ηϯαʹ0 lxͰͳ͍໨ඪর౓͕ཁٻ͞Εͨ৔߹ɼ

࠷খ఺౮ޫ౓Ͱ఺౮Λߦ͍ɼ߲໨2΁໭Δ ɹҎ্ͷಈ࡞ʹΑΓɼর໌ͱর౓ηϯαͷུ֓తͳҐ ஔؔ܎Λ೺Ѳ͠ɼর౓ηϯα͔Βԕ͍Ґஔʹ͋Δর໌

͸ɼޫ౓Λ཈͑Δ͜ͱͰɼ໨ඪর౓Λຬͨ͢ͱͱ΋ʹ লిྗͳঢ়ଶ΁ͱ଎΍͔ʹऩଋ͢Δɽ·ͨɼϢʔβ͕

཭੮͓ͯ͠Γɼ໌Δ͕͞ෆඞཁͳ৔ॴʹҐஔ͢Δর໌

͸ফ౮Λߦ͏͜ͱͰɼ͞Βʹߴ͍লΤωϧΪʔੑΛ࣮

ݱ͢Δɽ

Start

Accept Not Accept

Initial Luminance

Return to Previous Luminance

Accept Criterion

Get Illuminance & Power

Evaluation of Objective Function

Next Luminance Generation

Calculation of Correlation Coefficient

Next Evaluation of Objective Function Get Illuminance & Power

Turning on

Minimum Luminance

All Effective Sensors No Target Illuminance

Effective Sensor Target Illuminance

Turn off the Light Turn on the Light No

Yes

No Yes

No Yes

No Yes

Fig. 2. Control algorithm.

2.4 ճؼ෼ੳʹΑΔӨڹ౓೺Ѳ

஌తর໌γεςϜ͸ݸผর౓؀ڥΛఏڙ͢Δ͜ͱ Ͱɼলిྗͳঢ়ଶΛૉૣ࣮͘ݱ͢Δɽ͜ͷͨΊɼর໌

͕র౓ηϯαʹٴ΅͢Өڹ౓Λ೺Ѳ͢Δ͜ͱ͸ॏཁͰ

͋ΔɽͳͥͳΒɼӨڹ౓Λ೺Ѳ͢Δ͜ͱͰɼর໌͕େ

͖ͳӨڹΛ༩͑Δর౓ηϯαʹͷΈɼ࠷దԽͷର৅Λ ߜΔ͜ͱ͕Ͱ͖ΔͨΊͰ͋Δɽ

ANA/RCͰ͸ɼճؼ෼ੳΛ༻͍ͯর໌͕র౓ηϯ

αʹٴ΅͢Өڹ౓Λ೺Ѳ͢Δɽճؼ෼ੳ͸ɼઆ໌ม਺

ΛมԽͤͨ͞ࡍʹ؍ଌ஋͕ͲͷΑ͏ʹมԽ͢Δ͔ͱ͍

͏2ม਺ؒͷҼՌؔ܎ΛఆࣜԽ͢Δख๏Ͱ͋Δɽ͜ͷ ҼՌؔ܎͸ɼeq.(2)ʹࣔ͢આ໌ม਺xiͱ؍ଌ஋yjͷ

ؔ܎ࣜʹΑΓ໌ࣔͰ͖Δɽ

yj = rij×xi+β (2)

yɿ؍ଌ஋, xɿઆ໌ม਺,rɿճؼ܎਺βɿఆ਺߲

eq.(2)ʹࣔ͢Α͏ʹɼճؼ܎਺rij ͷେ͖͞ʹΑͬ

ͯҼՌؔ܎͕਺஋Խ͞ΕΔɽANA/RCͰ͸୳ࡧͷ1 ࢼߦʹ͓͚Δর໌ͷޫ౓มԽྔΛઆ໌ม਺xiɼর౓η ϯαͷর౓มԽྔΛ؍ଌ஋yjͱͯ͠ճؼ෼ੳΛߦ͏ɽ ճؼ෼ੳͷख๏ʹ͸࠷খೋ৐๏Λ༻͍ΔɽҎ্ͷॲཧ ʹΑΓɼর໌͕র౓ηϯαʹٴ΅͢Өڹ౓Λճؼ܎਺

ͱͯ͠਺஋Խ͢Δ͜ͱ͕ՄೳͱͳΔɽ

Fig. 3. Design of luminous intensity change rate.

2.5 ۙ๣ઃܭ

ANA/RCͰ͸ɼղͷ୳ࡧաఔʹ͓͍ͯہॴ࠷దղ

ʹؕΒͳ͍ͨΊʹɼ͢΂ͯͷর໌ʹ͓͍ͯಉҰͷۙ๣

Λ༻͍͍ͯΔͷͰ͸ͳ͘ɼঢ়گʹԠͯ͡ෳ਺ͷۙ๣Λ

࢖͍෼͚͍ͯΔɽ۩ମతʹ͸ɼFig. 3ʹࣔ͢Α͏ʹɼ ݱࡏͷޫ౓஋ͷ−1%͔Β12%·ͰͷൣғͰ࣍ޫ౓Λ ੜ੒͢Δ૿ޫۙ๣ʢAʣɼ−3%͔Β3%·Ͱͷதཱۙ

๣ʢBʣɼ͓Αͼ−10%͔Β1%·Ͱͷݮޫۙ๣ʢCʣ ͷ3छྨͷۙ๣Λ༻͍͍ͯΔɽͳ͓ɼ͜ΕΒͷۙ๣෯

͸ߏங͢Δ؀ڥʹԠͯ͡ద੾ͳ஋ͱͳΔΑ͏ʹνϡʔ χϯά͢Δඞཁ͕͋Γɼߏங͢Δ؀ڥ͝ͱʹ༧උ࣮ݧ

͕ඞཁͰ͋Δɽ

Ҏ্ͷ3छྨͷۙ๣Λɼeq.(3)ʹج͍ܾͮͯఆ͢Δɽ

Nij =

⎧⎪

⎪⎪

⎨

⎪⎪

⎪⎩

A rij≥T and Ici< Itj

B rij≥T and Ici≥Itj

C rij< T

(3)

Nijɿর౓ηϯαjʹΑΔর໌iͷۙ๣

Tɿᮢ஋, Aɿ૿ޫۙ๣ɼBɿதཱۙ๣ɼCɿݮޫۙ๣

rijɿর໌iʹର͢Δর౓ηϯαjͷճؼ܎਺

Icɿݱࡏর౓,Itɿ໨ඪর౓

eq.(3)ʹࣔ͢Α͏ʹɼ2.4અͰड़΂ͨճؼ܎਺͕ۙ

๣ܾఆʹ͓͍ͯॏཁͳύϥϝʔλͱͳΔɽͳͥͳΒর

໌͕র౓ηϯαʹٴ΅͢Өڹ౓Λճؼ܎਺͕ද͍ͯ͠

ΔͨΊͰ͋Δɽর౓ηϯα͕໨ඪর౓Λຬ͍ͨͯ͠ͳ

͍৔߹ɼͦͷর౓ηϯαʹ༩͑ΔӨڹ͕େ͖͍র໌ʹ

૿ޫۙ๣Λઃఆ͠ɼর໌͕૿ޫ͠΍͘͢͢Δɽٯʹɼ શͯͷর౓ηϯαʹରͯ͠༩͑ΔӨڹ͕খ͍͞র໌ʹ

͸ݮޫۙ๣Λઃఆ͢Δ͜ͱͰɼর໌͕ݮޫ͠΍͘͢͠ɼ ফඅిྗྔͷ࡟ݮΛਤΔɽҎ্ͷۙ๣ઃܭʹΑͬͯɼ

㕝ᮄ

Fig. 4. User interface of the intelligent lighting sys- tem (screen shot).

ہॴ࠷దղʹؕΓʹ͘͘ͳΔ͚ͩͰ͸ͳ͘ɼਝ଎ʹ໨

ඪর౓Λ࣮ݱ͢Δ͜ͱ͕ՄೳͱͳΔɽᮢ஋T͸eq.(1) ͷ΋ͷͱಉ͡஋Ͱ͋Δɽ

ͳ͓ɼর໌͸֤র౓ηϯαʹରͯ͠ɼಠཱͯۙ͠๣

ܾఆΛߦ͏ɽͭ·Γɼ1ͭͷর໌ث۩ʹ͖ͭɼর౓η ϯα͝ͱʹҟͳΔۙ๣͕ఆ·Δɽ͜ΕΒͷ͏ͪɼ࠷΋

૿ޫ܏޲ͷߴ͍ۙ๣Λɼͦͷর໌ث۩ͷۙ๣ͱ͢Δɽ

͢ͳΘͪɼ૿ޫۙ๣ʢAʣɼதཱۙ๣ʢBʣɼݮޫۙ๣

ʢCʣͷॱʹۙ๣ͷ༏ઌॱҐ͕ߴ͍ɽ

2.6 WebϢʔβΠϯλʔϑΣʔε

஌తর໌γεςϜͰ͸ɼ໨ඪর౓ͷઃఆͳΒͼʹɼ ࡏ੮ɾ཭੮৘ใͷೖྗΛ֤Ϣʔβ͕WebϢʔβΠϯ λʔϑΣʔεʢҎԼɼWeb UIͱ͢ΔʣΛ༻͍ͯߦ͏ɽ

Fig. 4ʹ஌తর໌γεςϜͷϢʔβΠϯλʔϑΣʔε

Λࣔ͢ɽ

֤Ϣʔβ͸ࣗ੮ʹண੮࣌ʹɼFig. 4ͷ࠲੮ҐஔΛද

ࣔͨ͠ϢʔβΠϯλʔϑΣʔεʹΞΫηε͢Δ͜ͱͰ

࠲੮഑ஔਤ͕දࣔ͞ΕΔɽͦͷத͔Βɼࣗ੮Λબ୒͢

Δ͜ͱͰɼબ୒ͨ͠࠲੮͕੺৭ͱͳΔͱಉ࣌ʹɼݸਓ

͝ͱͷϖʔδ͕දࣔ͞ΕΔɽදࣔ͞Εͨݸਓϖʔδ͔

Β໨ඪর౓΍ࡏ੮৘ใͷೖྗΛߦ͏ɽ໨ඪর౓ͷઃఆ

͸ɼ໨ඪর౓ઃఆཝΛΫϦοΫ͢Δ͜ͱͰ200 lxຖ ʹઃఆ͢Δ͜ͱ͕ՄೳͰ͋Δɽ·ͨɼඍௐ੔Λߦ͏৔

߹͸ɼ໨ඪর౓ઃఆཝԣͷϘλϯΛΫϦοΫ͢Δ͜ͱ

Ͱɼ50 lxຖͷઃఆ΋ՄೳͰ͋Δɽࡏ੮ɾ཭੮Ϙλϯ

ʹνΣοΫΛೖΕΔ͜ͱͰɼࡏ੮ɾ཭੮৘ใͷೖྗΛ ߦ͏ɽࡏ੮ϘλϯʹνΣοΫΛೖΕΔͱɼೖྗ͞Εͨ

໨ඪর౓͕ઃఆ͞ΕΔɽ·ͨɼ཭੮ϘλϯʹνΣοΫ

ΛೖΕΔͱɼ໨ඪর౓0 lx͕ઃఆ͞ΕΔɽ

࣮ΦϑΟεʹΑΔݕূ࣮ݧΛߦͬͨͱ͜Ζɼૣே΍

ਂ໷ͷ࣌ؒଳʹࡏ੮৘ใͷೖྗΛߦΘΕ͍ͯͳ͍͜ͱ ΑΓɼ΄ͱΜͲͷϢʔβ͸ৗʹࡏ੮ঢ়ଶͷ··Ͱ͋ͬ

ͨɽ·ͨɼ2010೥10݄ͷ1ϲ݄ؒʢ౔ɾ೔ɾॕ೔͸আ

͘ʣͷฏۉͰɼWeb UIΛ༻͍ͯࡏ੮ೖྗͷΈΛߦͬ

ͨϢʔβ͸5໊ɼ཭੮ೖྗͷΈΛߦͬͨϢʔβ͸4.65

໊ɼࡏ੮ɾ཭੮ͷ྆ํͷೖྗΛߦͬͨϢʔβ͸3.85໊ Ͱ͋ͬͨɽ͜ͷ͜ͱΑΓɼશϢʔβͷ໿1ׂͷΈ͔͠

ࡏ੮ɾ཭੮ʹԠͯ͡ɼࡏ੮ঢ়ଶͷೖྗΛߦ͍ͬͯͳ͍

͜ͱ͕Θ͔ͬͨɽ

࣮ࡍ͸Ϣʔβ͕཭੮΍ୀࣾʹΑͬͯɼෆࡏͱͳΓ໌

Δ͕͞ෆཁͱͳͬͨ৔ॴʹ͓͍ͯ΋ɼෆඞཁͳর໌͕

఺౮͍ͯ͠Δͱݴ͑Δɽͦ͏͍ͬͨ͜ͱ͔ΒɼলΤω ϧΪʔͷ؍఺͔Βվળ͢Δ΂͖Ͱ͋ΓɼϢʔβͷࡏ੮ɾ

཭੮৘ใͷೖྗঢ়گͷվળ͸ॏཁͳ՝୊Ͱ͋Δɽ

3. ICΧʔυʹΑΔࡏ੮؅ཧΛಋೖͨ͠஌తর໌γ εςϜ

3.1 ࡏ੮؅ཧͷඞཁੑ

લষͰड़΂ͨΑ͏ʹɼ࣮ΦϑΟεʹ͓͍ͯࡏ੮ɾ཭

੮৘ใͷೖྗΛద੾ʹߦΘΕ͍ͯͳ͍ͨΊʹɼ࣮ࡍ͸

Ϣʔβ͕ෆࡏͰ͋Δʹ΋͔͔ΘΒͣɼෆඞཁͳর໌͕

఺౮ͨ͠ঢ়ଶͷ··Ͱ͋Γɼ஌తর໌γεςϜͷলΤ ωϧΪʔੑ͕௿Լ͍ͯ͠Δɽͦ͜Ͱɼզʑ͸ࡏ੮ɾ཭

੮৘ใͷೖྗΛ޲্ͤ͞Δํ๏ͱͯ͠ɼϢʔβͷண੮

΍཭੮Λ൑அ͢Δண࠲ηϯαΛɼגࣜձࣾϓϩϏσϯ τͱڞಉͰࢼ࡞Λߦͬͨɽண࠲ηϯα͸ɼϢʔβͷ࠲

੮ʹઃஔ͠ɼѹྗ஋ͷมԽͰࡏ੮ɾ཭੮ͷ൑அΛߦ͏ɽ

Fig. 5ʹண࠲ηϯαΛࣔ͢ɽࢼ࡞ͨ͠ண࠲ηϯαΛ࣮

ΦϑΟεʹಋೖ͠ɼݕূΛߦͬͨɽϢʔβͷࡏ੮ɾ཭

੮ʹԠͯ͡ɼࡏ੮ɾ཭੮৘ใͷೖྗΛద੾ʹߦ͑Δ͜

ͱΛ֬ೝͨ͠ɽ͞Βʹɼண࠲ηϯαʹΑΓࡏ੮؅ཧΛ ߦ͏͜ͱͰɼෆࡏͱͳͬͨϢʔβͷর౓ηϯαʹͷΈ Өڹ͕͋Δর໌͕ফ౮͠ɼলΤωϧΪʔੑͷ޲্΋֬

ೝͨ͠⁷⁾ɽ

͔͠͠ɼண࠲ηϯα͸ࢼ࡞඼Ͱ͋ΔͨΊɼίετ໘

͔Βಋೖ΁ͷෑډ͸ߴ͍ɽ·ͨɼண࠲ηϯα͸Ϣʔβ

Fig. 5. Seat sensor.

ͷࡏ੮ɾ཭੮৘ใͷೖྗΛߦ͏͜ͱ͸ՄೳͰ͋Δ͕ɼ ͲͷϢʔβ͕ண੮͍ͯ͠Δ͔Λ೺Ѳ͢Δ͜ͱ͸Ͱ͖ͳ

͍ɽ͜ͷͨΊɼݻఆ੮ͷΦϑΟεͰ͸໰୊ͳ͍͕ɼϢʔ βͷ࠲੮͕ܾ·͍ͬͯͳ͍ϊϯςϦτϦΞϧΦϑΟε ͷ৔߹ɼ֤Ϣʔβͷண੮ҐஔʹɼͦͷϢʔβͷ೚ҙͷ

໨ඪর౓Λઃఆ͢Δ͜ͱ͸ࠔ೉Ͱ͋Δɽ

ͦ͜ͰɼΦϑΟεͷࣾһূʹଟ͘࢖༻͞ΕΔ܏޲ʹ

͋Δඇ઀৮ICΧʔυʢҎԼɼICΧʔυͱ͢ΔʣΛ༻

͍ͯɼϢʔβͷࡏ੮ɾ཭੮৘ใͷೖྗΛಋೖͨ͠஌త র໌γεςϜΛఏҊ͢Δɽ

3.2 γεςϜͷ֓ཁ

஌తর໌γεςϜ͸ɼγεςϜͷ੍ޚܗଶͱͯ͠෼

ࢄ੍ޚͱूத੍ޚͷ྆ํΛऔΔ͜ͱ͕Ͱ͖Δɽݱ࣌఺

Ͱ͸ɼίετͷ໰୊͔Βूத੍ޚܕͷγεςϜͷߏ੒

ΛऔΔɽͦͷͨΊɼຊγεςϜ͸র໌ث۩ɼর౓ηϯ αɼγεςϜ੍ޚ૷ஔɼిྗܭ͓ΑͼICΧʔυϦʔμ ΛωοτϫʔΫʹ઀ଓ͢Δ͜ͱͰߏ੒͢ΔɽICΧʔ υϦʔμ͸ɼর౓ηϯαͱซઃ͠ɼর౓ηϯαͱIC ΧʔυϦʔμͷରԠ͸ࣄલʹ೺ѲΛߦ͏΋ͷͱ͢Δɽ

·ͨɼ֤Ϣʔβ͸ɼݻ༗ͷIDΛׂΓ౰ͯΒΕͨIC ΧʔυΛอ࣋͢ΔɽࣾһূͳͲͷICΧʔυͷ໿9ׂ

͕FeliCa^*Λ࠾༻͍ͯ͠Δ͜ͱΑΓɼࠓճͷγεςϜ

͸FeliCaΛର৅ͱ͢Δɽ

γεςϜ੍ޚ૷ஔ͸ɼϢʔβ৘ใςʔϒϧͱর౓η ϯαςʔϒϧ͔Βߏ੒͞ΕΔσʔλϕʔεΛ͍࣋ͬͯ

ΔɽϢʔβ৘ใςʔϒϧ͸ICΧʔυʹׂ౰ͯΒΕͨ

ݻ༗ͷIDʢϢʔβIDʣΛओΩʔͱ͠ɼࢯ໊ɼ໨ඪর

౓ͷ߲໨͔ΒͳΔɽ·ͨɼর౓ηϯαςʔϒϧ͸ηϯ αIDΛओΩʔͱ͠ɼϢʔβIDɼࡏ੮ɾ཭੮৘ใͷ߲

∗FeliCa͸ɼιχʔגࣜձࣾͷొ࿥঎ඪͰ͋Δɽ

໨͔ΒͳΔɽ࣍અʹ੍ޚͷྲྀΕΛࣔ͢ɽ

3.3 ੍ޚͷྲྀΕ

֤Ϣʔβ͕ண੮࣌ʹص্ͷICΧʔυϦʔμʹIC ΧʔυΛஔ͘͜ͱͰɼγεςϜ੍ޚ૷ஔ͸ωοτϫʔ Ϋʹૹ৴͞ΕͨϢʔβIDͱண੮࠲੮৘ใʢηϯαIDʣ Λड͚औΔɽड͚औͬͨ৘ใΛجʹɼর౓ηϯαςʔ ϒϧͷ֘౰͢ΔηϯαIDʹϢʔβIDͱࡏ੮৘ใΛ

ొ࿥͢ΔɽҰํɼ཭੮࣌ʹ֤Ϣʔβ͕ICΧʔυΛIC ΧʔυϦʔμ͔ΒऔΓআ͘͜ͱͰɼ཭੮࠲੮ʹؔ͢Δ

৘ใΛωοτϫʔΫʹૹ৴͢Δɽͦͷ৘ใΛγεςϜ

੍ޚ૷ஔ͕൑அ͠ɼর౓ηϯαςʔϒϧͷ֘౰͢Δη ϯαIDʹ཭੮৘ใΛొ࿥͢Δɽ

ICΧʔυ͕ICΧʔυϦʔμ্ʹ͋Δ͔ͷ༗ແͷ൑

அʹ͍ͭͯड़΂ΔɽຊγεςϜͷICΧʔυϦʔμ͕ɼ Ұఆظؒ͝ͱʹICΧʔυͷ༗ແΛݕࡧʢҎԼɼPolling ͱ͢ΔʣΛߦͳ͏ɽICΧʔυϦʔμʹICΧʔυ͕ஔ

͔Ε͍ͯͨ৔߹ɼPollingͷϨεϙϯεσʔλͱͯ͠ɼ

੡଄IDʢҎԼɼIDmͱ͢ΔʣΛऔಘ͢ΔɽҰํɼஔ

͔Ε͍ͯͳ͍৔߹ɼPollingͷϨεϙϯεσʔλ͕औ ಘ͞Εͳ͍ɽ͜ΕΛجʹɼICΧʔυͷ༗ແΛ൑அ͢

Δɽ·ͨɼICΧʔυ͕ஔ͔Ε͍ͯͨ৔߹ʹऔಘ͞Ε ΔIDm͸ɼΧʔυ੡଄࣌ʹҰ౓͚ͩઃఆ͞Εɼઃఆ ޙͷมߋ͸ແ͍ɽ·ͨɼઃఆ஋͸͢΂ͯ੡඼͝ͱʹن ఆ͞ΕΔɽ͜ͷͨΊɼ͜ͷIDmΛϢʔβIDͱͯ͠࢖

༻͢Δ͜ͱ͸໰୊͕ͳ͍ͱߟ͑Δɽ

͜ͷΑ͏ʹɼ੍ޚΛߦͳ͏͜ͱͰɼண੮࣌͸ண੮࠲

੮Ґஔͷࡏ੮৘ใΛࡏ੮ͱ͠ɼ೚ҙͷ໨ඪর౓Λઃఆ Λߦ͏ɽ·ͨɼ཭੮࣌͸཭੮࠲੮Ґஔͷࡏ੮৘ใΛ཭

੮ͱ͠ɼ໨ඪর౓0 lxͷઃఆΛߦ͏ɽ

3.4 ICΧʔυʹΑΔࡏ੮؅ཧͷಛ௃

ICΧʔυʹΑΔࡏ੮؅ཧΛಋೖͨ͠஌తর໌γε ςϜͷେ͖ͳಛ௃͸ɼϊϯςϦτϦΞϧΦϑΟεͷΑ

͏ͳϢʔβબ୒࠲੮ʹରԠ͢Δ͜ͱ͕ՄೳͰ͋Δͱ͍

͏఺Ͱ͋Δɽ

ຊγεςϜ͸ɼϢʔβ͕ICΧʔυΛண੮࠲੮ʹઃ

ஔ͞Ε͍ͯΔICΧʔυϦʔμʹஔ͘͜ͱͰɼICΧʔ υݻ༗ͷIDͱண੮࠲੮৘ใΛωοτϫʔΫʹૹ৴͢

Δɽ͜ΕʹΑΓɼγεςϜ͸ࣗಈతʹϢʔβ͕ɼͲͷ

Fig. 6. Experiment Environment.

Fig. 7. Illuminance sensor and IC card reader.

࠲੮ʹ͍Δͷ͔Λ೺Ѳ͢Δ͜ͱ͕ՄೳͰ͋Δɽ

4. ICΧʔυʹΑΔࡏ੮؅ཧΛಋೖͨ͠஌తর໌γ εςϜͷ༗ޮੑධՁ

4.1 ࡏ੮ɾ཭੮ঢ়گͷݕূ

4.1.1 ࣮ݧ֓ཁ

ఏҊγεςϜͷ༗ޮੑΛݕূ͢ΔͨΊʹɼWeb UI ʹΑΔࡏ੮ɾ཭੮৘ใͷೖྗΛߦ͏஌తর໌γεςϜ ͱͷࡏ੮؅ཧͷ࣮ݱ౓߹͍ͷൺֱΛߦ͏ɽ࣮ݧ͸ɼେ

ֶʹ͓͚ΔֶੜډࣨʹԾઃఱҪΛઃ͚ɼFig. 6ʢAʣ͓

ΑͼʢBʣʹࣔ͢؀ڥΛߏங͠ɼனന৭র໌10౮͓Α ͼর౓ηϯα9୆Λ༻͍ͯߦ͏ɽఏҊγεςϜͷ࣮ݧ

࣌͸ɼ֤র౓ηϯαͱซઃͯ͠ɼICΧʔυϦʔμΛ

ઃஔͨ͠ɽICΧʔυϦʔμͱর౓ηϯαͷઃஔঢ়گ ΛFig. 7ʹࣔ͢ɽ

Fig. 8. History of seated peopleʢWeb UIʣ.

·ͨɼ࣮ࡍʹϢʔβ͕ࡏ੮͔཭੮͔ͷݕূΛߦ͏ͨ

Ίʹɼ֤Ϣʔβͷ࠲੮ʹண࠲ηϯαΛઃஔͨ͠ɽFig.

6ʢBʣʹ͸ɼܬޫ౮ٴͼর౓ηϯαͷҐஔؔ܎Λࣔ͠

͓ͯΓɼਤதͷܬޫ౮ԣͷ൪߸͸ܬޫ౮൪߸Λɼর౓

ηϯαԣͷΞϧϑΝϕοτ͸ηϯαͷࣝผ໊ͳΒͼʹ

ඃݧऀ໊Λද͢ɽ

2011೥9݄5೔͔Βಉ೥10݄4೔ͷظؒʹɼIC ΧʔυΛ༻͍ͨࡏ੮؅ཧΛಋೖͨ͠஌తর໌γεςϜ ͷ࣮ݧΛߦ͍ɼ2011೥10݄5೔͔Β11݄4೔ͷظ

ؒʹɼWeb UIΛ༻͍ͯࡏ੮؅ཧΛ࣮ݱ͢Δ஌తর໌

γεςϜͷ࣮ݧΛߦͬͨɽ྆γεςϜʹ͓͍ͯɼࡏ੮

؅ཧͷ࣮ݱ౓߹͍Λݕূ͢Δɽͭ·Γɼண࠲ηϯαͰ ಘΒΕͨϢʔβͷࡏ੮ɾ཭੮ঢ়گͱൺֱ͠ɼͲͷఔ౓

ࡏ੮ɾ཭੮ͷ৘ใ͕ਖ਼֬ʹೖྗ͞Ε͍͔ͯͨͷݕ౼Λ ߦ͏ɽ

4.1.2 ࣮ݧ݁Ռ͓Αͼߟ࡯

Web UIΛ༻͍ͯࡏ੮؅ཧΛߦͬͨ৔߹ͷ͋ΔҰ೔

ͷࡏ੮৘ใೖྗऀ਺ͷཤྺΛFig. 8ʹɼICΧʔυΛ

༻͍ͯࡏ੮؅ཧΛߦͬͨ৔߹ͷ͋ΔҰ೔ͷࡏ੮৘ใೖ

ྗऀ਺ͷཤྺΛFig. 9ʹࣔ͢ɽFig. 8ͳΒͼʹFig.

9ͷԣ࣠͸࣌ؒɼॎ࣠͸ࡏ੮ऀ਺Λࣔ͢ɽ·ͨɼTable 1ʹɼ֤ΠϯλʔϑΣʔεʹ͓͚Δؼ୐࣌ͷ཭੮৘ใ

ೖྗ཰Λࣔ͢ɽTable 2ʹɼ֤࣮ݧظؒʹ͓͚Δ֤Π ϯλʔϑΣʔεͱண࠲ηϯαͷࡏ੮৘ใೖྗঢ়گͷҰ க౓Λࣔ͢ɽ

Fig. 8ΑΓɼWeb UIΛ༻͍ͯࡏ੮؅ཧΛߦͬͨ৔

߹͸ɼϢʔβ͕ෆࡏͳਂ໷ͷ࣌ؒଳʹ͓͍ͯࡏ੮ೖྗ

͕ҡ࣋͞Εͨঢ়ଶͰ͋ΔϢʔβ͕͍Δ͜ͱ͕Θ͔Δɽ

·ͨɼࡏ੮΍཭੮ʹԠͯ͡ɼϢʔβ͕ࡏ੮৘ใͷೖྗΛ ਖ਼֬ʹߦ͍ͬͯͳ͍͜ͱ͕Θ͔ΔɽҰํɼFig. 9ΑΓɼ

Fig. 9. History of seated peopleʢIC cardʣ.

Table 1. Input rate on going home.

IC card[%] Web UI[%]

User A 91.7 42.9

User B 100.0 64.0

User C 100.0 84.6

User D 100.0 93.8

User E 100.0 100.0

User F 100.0 93.3

User G 100.0 57.1

User H 100.0 93.8

User I 100.0 100.0

ICΧʔυΛ༻͍ͯࡏ੮؅ཧΛߦͬͨ৔߹Ͱ͸ɼϢʔ β͕ෆࡏͳ࣌ؒଳʹ͓͍ͯɼࡏ੮৘ใͷೖྗऀ਺͸0

໊Ͱ͋Γɼؼ୐࣌ʹ཭੮৘ใͷೖྗ͕ਖ਼֬ʹߦΘΕͯ

͍Δ͜ͱ͕෼͔Δɽ·ͨTable 1ΑΓɼಛʹICΧʔ υΛ༻͍ͯࡏ੮؅ཧΛߦ͏͜ͱʹΑΓɼؼ୐࣌ͷ཭੮

৘ใͷೖྗΛվળͰ͖ͨͱݴ͑Δɽ

·ͨɼTable 2ΑΓɼ΄ͱΜͲͷϢʔβʹ͓͍ͯɼ

ICΧʔυʹΑΔࡏ੮؅ཧΛߦͬͨ৔߹ͷ΄͏͕ɼWeb UIʹΑΔ؅ཧͱൺ΂ɼண࠲ηϯαͱͷҰக౓͕ߴ͘ɼ Ϣʔβͷࡏ੮ɾ཭੮ʹԠͨ͡৘ใೖྗ͕ߦΘΕɼࡏ੮

؅ཧͷ޲্Λ࣮ݱͰ͖ͨ͜ͱ͕Θ͔ΔɽϢʔβF͕

Web UIར༻࣌ͷํ͕Ұக཰ߴ͔ͬͨ͜ͱͳΒͼʹɼ

ϢʔβD΍ϢʔβH͕ICΧʔυ࢖༻࣌ͱWeb UI࢖

༻࣌Ͱ͕ࠩେ͖͘ग़ͳ͔ͬͨཧ༝ͱͯ͠ɼݚڀࣨ଺ࡏ

͕࣌ؒ୹͔ͬͨ͜ͱ͕ݪҼͱͯ͠ߟ͑Δɽ

͜ΕΒͷ݁Ռ͔Βɼࡏ੮ɾ཭੮৘ใͷೖྗʹICΧʔ υΛ༻͍Δ͜ͱ͸ɼࡏ੮؅ཧͷ޲্ʹ༗ޮͰ͋Δͱݴ

Table 2. Concordance rate for seat sensor.

IC card[%] Web UI[%]

User A 85.5 48.1

User B 92.2 59.8

User C 95.4 71.0

User D 94.5 89.0

User E 85.5 77.7

User F 79.1 82.5

User G 91.0 57.0

User H 89.9 85.5

User I 94.7 81.5

͑Δɽ

4.2 লΤωϧΪʔੑͷݕূ

4.2.1 ࣮ݧ֓ཁ

ICΧʔυʹΑΔࡏ੮؅ཧΛಋೖͨ͠஌తর໌γε ςϜʹΑΔলΤωϧΪʔੑͷݕূΛߦ͏ɽFig. 6ͷ؀

ڥΛ໛ٖ͠ɼ4.1અͷ࣮ݧͰಘͨࡏ੮৘ใͷཤྺΛج ʹɼࡏ੮ɾ཭੮ͷεέδϡʔϧΛ༩͑ɼγϛϡϨʔγϣ ϯ࣮ݧΛߦ͏ɽ࣮ݧͰ༻͍ͨࡏ੮ɾ཭੮εέδϡʔϧ

͸ɼFig. 8ͳΒͼʹFig. 9Ͱ͋Δɽண࠲ηϯαΛ࢖༻

ͨ͠৔߹ͱൺ΂ɼͲͷఔ౓ফඅిྗྔʹ͕ࠩੜ͡Δ͔

ΛجʹɼICΧʔυʹΑΔࡏ੮؅ཧͱWeb UIʹΑΔ ࡏ੮؅ཧΛߦͳͬͨ৔߹ͷলΤωϧΪʔੑೳͷൺֱΛ ߦ͏ɽ

·ͨɼ໨ඪর౓͸ɼ࣮ݧظؒ಺ʹ֤Ϣʔβ͕ઃఆ࣌

ؒͷ௕͔ͬͨ΋ͷΛ࠾༻ͨ͠ɽϢʔβAɼBɼCɼEɼ H͓ΑͼI͸500 lxɼϢʔβD͸400 lxɼϢʔβG

͸300 lxɼϢʔβF͸250 lxͱͨ͠ɽ

4.2.2 ࣮ݧ݁Ռ͓Αͼߟ࡯

Web UIʹΑΔࡏ੮؅ཧΛߦͬͨ৔߹ͷফඅిྗྔ

ͷਪҠΛFig. 10ʹࣔ͠ɼICΧʔυʹΑΔࡏ੮؅ཧ Λߦͬͨ৔߹ͷফඅిྗྔͷਪҠΛFig. 11ʹࣔ͢ɽ Fig. 10ͳΒͼʹɼFig. 11ͷԣ࣠͸࣌ؒɼॎ࣠͸ফඅి

ྗྔΛඦ෼཰Ͱࣔ͢ɽΦϑΟεͰ͸ɼص্໘র౓750 lxΛຬͨ͢ͱఆΊΒΕ͍ͯΔͨΊ⁸⁾ɼ͜ΕΛ࣮ݱ͢Δ

Fig. 10. History of electric power consumption ʢWeb UIʣ.

Fig. 11. History of electric power consumptionʢIC cardʣ.

఺౮ঢ়ଶͰͷফඅిྗྔΛ100 %ͱͨ͠ɽ

Fig. 8ͳΒͼʹFig. 10ΑΓɼWeb UIʹΑΔࡏ੮

؅ཧΛߦͬͨ৔߹ɼϢʔβͷࡏ੮ɾ཭੮ʹରԠͯ͠ਖ਼

͘͠ࡏ੮৘ใͷೖྗ͕ߦΘΕ͍ͯͳ͍ɽ͜ΕʹΑΓɼ 17࣌ࠒ͔Β18࣌ࠒͷ࣮ࡍ͸ɼϢʔβ͕ෆࡏͰ͋Δ࣌

ؒଳͰ͋ͬͯ΋ɼ2໊ͷϢʔβ͕ࡏ੮৘ใΛೖྗͨ͠

··Ͱ͋ΔͨΊʹɼর໌͕ফ౮͢Δ͜ͱͳ͘ɼ35 %ఔ

౓ͷফඅిྗྔΛফඅ͍ͯ͠Δ͜ͱ͕Θ͔Δɽ͜ͷ݁

Ռɼண࠲ηϯαʹΑΔࡏ੮؅ཧΛ૝ఆͨ͠৔߹ͱൺֱ

͠ɼলΤωϧΪʔੑ͕໿31 %௿Լ͍ͯ͠Δ͜ͱ͕Θ

͔ͬͨɽ

ҰํͰɼFig. 9ͳΒͼʹFig. 11ΑΓɼICΧʔυΛ

༻͍ͨࡏ੮؅ཧΛߦͳͬͨ৔߹ɼϢʔβͷࡏ੮ɾ཭੮ ʹରԠͯ͠ൺֱతਖ਼͘͠৘ใೖྗ͕ߦͳΘΕ͍ͯΔɽ

ͦͷͨΊɼফඅిྗྔͷਪҠ͸ɼண࠲ηϯαʹʹΑΔ ࡏ੮؅ཧΛ૝ఆͨ͠৔߹ͱࠅࣅͨ͠ਪҠΛߦͳ͍ͬͯ

Δ͜ͱ͕Θ͔Δɽ݁Ռɼண࠲ηϯαʹΑΔࡏ੮؅ཧΛ

૝ఆͨ͠৔߹ͱൺֱ͠ɼলΤωϧΪʔੑ͕໿5 %ͷ௿

ԼͰऩ·Δ͜ͱ͕Θ͔ͬͨɽ

͜ͷ݁Ռ͔ΒɼICΧʔυʹΑΔࡏ੮؅ཧΛಋೖ͢

Δ͜ͱͰɼैདྷͷWeb UIʹΑΔࡏ੮؅ཧΛߦͳͬͨ

৔߹ͱൺֱͯ͠ɼ໿26 %ͷলΤωϧΪʔੑ޲্͕͋

Δ͜ͱ͕Θ͔ͬͨɽ

5. ݁࿦

͜Ε·Ͱɼ೚ҙͷ৔ॴʹ೚ҙͷ໌Δ͞Λఏڙ͢Δ͜

ͱͰɼߴ͍লΤωϧΪʔੑΛ࣮ݱ͢Δ஌తর໌γες Ϝͷ༗ޮੑ͕࣮ݧࣨʹ͓͍ͯ֬ೝ͞Ε͍ͯͨɽ࣮༻Խ ʹΉ͚࣮ͯΦϑΟεͰͷݕূ͕ඞཁͰ͋Γɼ࣮ࡍʹγ εςϜͷಋೖΛߦͳͬͨɽͦͷ݁ՌɼҰ෦ͷϢʔβͷ Έ͕ࡏ੮ɾ཭੮৘ใͷೖྗΛߦ͍ͬͯΔͱ͍͏ݱঢ়Ͱ

͋Δ͜ͱ͕Θ͔ͬͨɽͦͷͨΊɼ࣮ࡍ͸Ϣʔβ͕ෆࡏ Ͱ͋Δʹ΋͔͔ΘΒͣɼෆඞཁͳর໌͕఺౮͍ͯ͠Δ

ͨΊʹɼ஌తর໌γεςϜͷলΤωϧΪʔੑ͕௿Լ͠

͍ͯͨɽ

ͦ͜Ͱɼैདྷ͸ࡏ੮ɾ཭੮৘ใͷೖྗΛWeb UIΛ

༻͍ͯߦͳ͍͕ͬͯͨɼͦΕʹ୅ΘΓΦϑΟεͷࣾһ

ূʹଟ͘࢖༻͞ΕΔඇ઀৮ICΧʔυΛ༻͍ͯɼࡏ੮ɾ

཭੮৘ใͷೖྗΛ࣮ݱ͢Δ஌తর໌γεςϜΛఏҊ͠

ͨɽ࣮ݧγεςϜΛߏங͠ɼݕূ࣮ݧΛߦ͍ɼఏҊγ εςϜͷ༗ޮੑʹ͍ͭͯݕ౼ΛߦͬͨɽҎԼʹɼຊݚ ڀʹΑΓಘΒΕͨ݁࿦Λࣔ͢ɽ

• ࡏ੮ɾ཭੮৘ใͷೖྗΛICΧʔυʹ͢Δ͜ͱͰɼ

ैདྷγεςϜʹൺ΂ͯɼϢʔβͷࡏ੮ɾ཭੮ʹԠ

ͨ͡৘ใೖྗͷ޲্Λ֬ೝͨ͠ɽ

• ݕূ࣮ݧͰಘͨࡏ੮ɾ཭੮εέδϡʔϧΛجʹɼ লΤωϧΪʔੑͷγϛϡϨʔγϣϯΛߦ͍ɼఏҊ γεςϜʹΑΓলΤωϧΪʔੑ͕޲্͢Δ͜ͱΛ

֬ೝͨ͠ɽ

͜ΕʹΑͬͯɼϢʔβͷࡏ੮ɾ཭੮৘ใͷೖྗΛվ ળ͢Δ͜ͱͰɼ஌తর໌γεςϜͷߴ͍লΤωϧΪʔ

ੑΛൃش͢Δ͜ͱ͕ՄೳʹͳΔɽ

ຊݚڀͷҰ෦͸ɼಉࢤࣾେֶཧ޻ֶݚڀॴݚڀॿ੒

ۚͷॿ੒Λड͚ͯߦΘΕͨɽ

ࢀɹߟɹจɹݙ

1) େྛ࢙໌, ෌ా࿨޺,෰෦ᘯࢠ, Տ಺ඒࠤ,Լా޺,ੴҪ༟߶,

ࣉ໺ਅ໌,٢઒ᒇ࿨, “ΦϑΟεϫʔΧͷϓϩμΫςΟϏςΟվ ળͷͨΊͷ؀ڥ੍ޚ๏ͷݚڀ ʵ র໌੍ޚ๏ͷ։ൃͱ࣮ݧతධ Ձ”, ώϡʔϚϯΠϯλʔϑΣʔεγϯϙδ΢Ϝ, [1322],151- 156(2006).

2) ੢ݪ௚ࢬ, ాล৽Ұ, “தఔ౓ͷߴԹ؀ڥԼʹ͓͚Δ஌తੜ࢈

ੑʹؔ͢Δඃݧऀ࣮ݧ”,೔ຊݐஙֶձ؀ڥܥ࿦จू, [568],33- 39(2003).

3) Peter R. Boyce, Neil H. Eklund, S. Noel Simpson, “Indi- vidual Lighting Control: Task Performance”, Mood and Il- luminance JOURNAL of the Illuminating Engineering So- ciety, 131-142(2000).

4) M.MikiɼT.HiroyasuɼK.Imazato, “Proposal for an intel- ligent lighting system, and verification of control method effectiveness”, Proc. CIS, 520-525(2004).

5) ࡾ໦ޫൣ, “஌తর໌γεςϜͱ஌తΦϑΟε؀ڥίϯιʔγΞ Ϝ”,ਓ޻஌ೳֶձࢽ,22[3],399-410(2007).

6) S.Tanaka, M.Miki, T.Hiroyasu, M.Yoshikata, “An Evolu- tional Optimization Algorithm to Provide Individual Illu- minance in Workplaces”, Proc IEEE Int Conf Syst Man Cybern,2,941-947(2009).

7) େֶ๏ਓಉࢤࣾେֶ,גࣜձࣾࡾҪ෺࢈ઓུݚڀॴ, “ฏ੒20

೥౓ʙฏ੒22೥౓੒ՌใࠂॻΤωϧΪʔ࢖༻߹ཧԽٕज़ઓུ

త։ൃ/ΤωϧΪʔ༗ޮར༻ج൫ٕज़ઌಋݚڀ։ൃ/ࣗ཯෼ࢄ࠷

దԽΞϧΰϦζϜΛ༻͍ͨলΤωܕর໌γεςϜͷݚڀ։ൃ”, No.20110000000875(2011).

8) ΦʔϜࣾ,র໌ֶձ, “র໌ϋϯυϒοΫ”, (2003).