【國際譯文】科技趨勢如何塑造環安衛監控的未來 How Technology Megatrends Are Shaping the Future of Safety, Health, and Environmental Monitoring


   
 (picture from OHS Online)

隨著現代科技迅速發展,智慧型手機等等的無線設備、低成本感應器的出現、大數據與群眾外包趨勢,都將改變我們對工作場所的風險評估與危害監控方式。


本文一次列出各種新科技趨勢,並實際針對各種科技在環安衛領域的應用舉出例子,非常值得各位閱讀,並思考新科技在您所處的領域能否玩出什麼新的花樣?

作者 :Rob Brauch
翻譯:威煦軟體


無線設備的整合、低成本感應器、大數據與群眾外包,都將改變我們對工作場所的風險評估方式。
The convergence of wireless devices, low-cost sensors, Big Data, and crowdsourcing will change the way you assess risk in your workplace.

隨著消費者導向的技術迅速發展,針對工作場所危害的新式監控、測量和控制方法也不斷出現,相信很快就會帶來各項風險評估與可能危害暴露情形的替代方案。像穩定成長的物聯網(IoT)這樣的科技新趨勢,讓如今的電子裝置能夠線上即時定位,並可與其他生活中常用的消費性產品整合,這樣的改變已經開始影響我們對工作環境的及時評估。
New ways to monitor, measure and control workplace hazards are emerging with the rapid development of consumer-driven technologies, and soon this will result in alternative ways to assess risk and exposure to a wide variety of potentially harmful conditions. Technology megatrends, including the rapid growth of the Internet of Things (IoT), where electronic devices become instantly addressable online and can "integrate" with other consumer products we use every day, are already starting to have influence on how we can assess the working environment in real time.

智慧型手機和平板電腦 (或稱手持設備,HHDs)的全球化普及,對我們日常生活中不同層面都造成非常顯著的影響,這些設備幾乎已成為我們的分身,也是我們溝通、獲得信息、記錄周遭世界的主要方式。例如我們使用手持設備,除了可以用「過時的撥打電話」方式與人溝通外,還可以傳送訊息和電子郵件,甚至可以透過網路環境,彈指之間就能獲取各領域的知識:從SDSs 到美國國家職業安全衛生研究所(NIOSH)採用的抽樣方法,甚至於美國職業安全與健康管理局(OSHA)訂定的規範,都輕鬆掌握在我們的手中。

目前已有手機APP軟體可以模仿我們在工作場所使用的某些監控裝置功能 (例如噪音計),雖然正確性與可追蹤性尚未滿足需求,但若要解決「何時何地需要進行個人噪音管制,以符合聽力保護標準」的問題,就非常實用。除此之外還有越來越多應用,從運用相機和視頻功能在手持裝置上記錄分享我們最喜歡的餐廳所販售的美味甜點,到記錄工作條件、實務作法和危害,再以電子郵件或訊息將它的重要性傳遞給別人等等。
The universal adoption of smartphones and tablets (otherwise known as hand-held devices, or HHDs) has dramatically affected our daily routines on so many levels, to the point where these devices have almost become extensions of ourselves. They are the primary way we communicate, obtain information, and document the world around us--for example, we use them to communicate using text and email, in addition to "old-fashioned phone calls," and we can access the entire "webisphere" of knowledge almost instantly: Everything from SDSs to NIOSH sampling methods to OSHA regs are at our fingertips. There are now apps that can mimic the performance of certain monitoring devices we use in the workplace, such as sound-level meters, (albeit not with the accuracy and traceability needed for compliance purposes), and these have proven to be very useful for determining where and when to perform personal noise dosimetry for meeting regulatory compliance and hearing conservation objectives. And more and more, we use the camera and video capabilities in our HHDs to document and share not just the fanstastic desert we enjoyed at our favorite restaurant, but also to illustrate workplace conditions, practices, and hazards—and then to email or text these to others to emphasize their importance.

這些替代技術的應用意識在環安衛產業中不斷提升,其背後推手是美國國家職業安全衛生研究所(NIOSH)主任,約翰霍華德醫生。他在2014年8月推出了NIOSH中心直接讀取和傳感器技術,並表示:「直接讀取設備和智慧型手機的應用程序未來可在工業衛生和安全評估領域發展出革命性的新做法。」
Growing awareness of this alternative use of technology by the safety and health profession is behind the recent launch of the NIOSH Center for Direct Reading and Sensor Technologies in August 2014. According to Dr. John Howard, the director of NIOSH, "The future of direct-reading devices and smartphone applications may help to revolutionize the practice of industrial hygiene and safety evaluations."


無線裝置+遙控儀器x大數據=更好的結果
Wireless Devices + Monitoring  Instruments x Big Data = Better Outcomes

現今越來越多工業安全相關的無線監控裝置選擇將數據傳送到中央控制中心(例如氣體和輻射監視設備),近期更有個人顯示器開始配置無線通信規格。這些改變讓環安衛業者得以透過遠端一次監控多位勞工,當員工的危害暴露值偏高或甚至超過標準時,就可以及時警惕。
Today, there are a growing number of safety and industrial hygiene monitoring devices that already transmit data wirelessly to a central hub (devices such as area gas and radiation monitors). More recently, other personal monitors are beginning to add wireless communications to their performance specifications. This will allow safety and health practitioners to remotely monitor multiple workers in real time and be alerted when exposure levels become significant or excessive.

這些新技術的開展,建立在手持設備大量增加,以及利用藍牙和Wi-Fi把傳統用來偵測危害暴露的設備與智慧型手機或平板電腦結合所製造的強大力量上。再加上小尺寸、低耗電、低成本感應器的發展,將會大大開拓安全衛生人員的無限可能,可以更即時、更不費力地監控的更廣的區域和更多的勞工人數。

接著,透過使用手持裝置用電子郵件把多個工人與多重危害監測的結果用電子郵件傳送到企業伺服器,最終將會淘汰傳統緩慢的監控方法,也就是手動從監視器或其他儀器,將資料一個一個下載到個人電腦,整理成獨立的報告,然後擷取重要的部分(例如列入醫療或安全監控數據庫)。
These new technologies will leverage off of the proliferation of HHDs and the incredible power they possess by marrying instruments that are typically used for exposure assessment with your smartphone or tablet using Bluetooth and Wi-Fi. This, along with the development of small, low-power, low-cost sensors opens up tremendous possibilities for safety and health professionals to multiply their ability to screen work areas for potential hazards and monitor far greater numbers of workers in real time with far less effort. Then, by using the HHD as a bridge to your corporate server through the use of email to transfer results of monitoring these multiple hazards on multiple workers, the traditional "speed bumps" of having to manually download reports one by one from a monitor or other instrument to a PC, generating individual reports, and then stripping out the important parts of the report (for inclusion in a medical or safety surveillance database, for example) will eventually disappear.

近期另一項將永遠改變安全健康領域的趨勢,是利用資料發掘和大數據作為安全健康的分析管理工具。隨著急速增加的相關應用範例,資料準確度大幅提升,相關危害因子暴露量的決策也將有更多可參考的統計分析數據。這些改變將有助於識別異常值 (也就是因暴露於過多危害而受到影響的個人、流程和做法),也因為擁有了更快速、更多元且準確的勞工暴露數據和評估,將能給予醫生和管理人員更多信心。
The use of data mining and the emergence of Big Data as an analysis and management tool is yet another recent megatrend that will forever change the safety and health profession. As the number of samples that can be taken in the field increases dramatically, the accuracy of the results will grow and decisions taken to limit exposures will be based more on the statistical analysis of a far greater range of samples. This will help to identify outliers (individuals, processes, and practices that result in greater exposure levels), as well as give confidence to the practitioner and management that they are capturing a more accurate assessment of the workers’ exposures through a variety of operating conditions and work rates.


從數字看安全 (體制外的群眾外包和內部群眾外包)
Safety by the Numbers (Crowdsourcing Beyond the Perimeter and In-house Crowdsourcing)

什麼是群眾外包? 根據維基百科的定義,它是「請求一群人的協助,尤其是一群網友而非傳統的員工或供應商,從而獲取所需之服務、想法或內容的過程」。另外根據Google的定義,「執行群眾外包」是「透過付費或未付費爭取到的眾人服務,進而獲取信息或特定任務項目的產出,通常經由網路完成。」
What is Crowdsourcing? According to one definition, it is "the process of obtaining needed services, ideas, or content by soliciting contributions from a large group of people, and especially from an online community, rather than from traditional employees or suppliers" (Wikipedia). "To crowdsource" is defined by Google as: "obtain information or input into a particular task or project by enlisting the services of a number of people, either paid or unpaid, typically via the Internet."

有個例子可以看出智慧型手機如何影響我們日常生活,透過這個我們每天攜帶在身邊的裝置,我們可以測量週遭環境噪聲污染的程度並產出報表。這也說明了工作環境監控將非常可能產生大規模的變革。兩個利用群眾外包來解決環境噪音污染的實務做法,更說明了裝置與無線APP整合後所產生的力量,一個是“噪音錶Noise Watch”,另一個是“噪音頻道NoiseTube”,兩個都使用手機和平板電腦內建的麥克風、聲位儀和GPS定位數據,把即時測量的噪音情形顯示在地圖上,就像你會把現在的交通路況,用綠色,黃色,紅色等顏色視覺化在地圖上一樣,只不過如今換成顯示噪音的程度。

群眾外包的另一個有趣的發展,是利用智慧型手機的攝像鏡頭,要求用戶面對固定方向,對著地平線拍照,透過日出和日落的相對朦朧程度作為衡量空氣污染狀況的指標。雖然群眾並不打算把這些應用程式的數據用來訴訟或挑戰監管單位,但隨著時間推移,它們的確提供了很好的汙染測量指標,並打造了一個「裝置分析的趨勢」。

從這些例子中,不難想像一個擁有許多廠區的大公司,當各廠區運作規模與型態都相似的情況下,能如何運用「內部群眾外包」的概念,更透徹地了解各廠區的運作流程和趨勢,讓各廠區能有更高的一致性,且都能避免工人陷於危害暴露中,或造成環境污染。
An example of how smartphones have transfigured our daily lives involves using the devices we all carry every day to measure and report levels of noise pollution in the ambient environment. This illustrates the potential for changes in monitoring the working environment, as well. Two applications of crowdsourcing to address environmental noise pollution illustrate the power of device integration with wireless apps: One is "Noise Watch" and the other is "NoiseTube"; both use the microphone and sound-level meter type applications available for phones and tablets with their built-in GPS location data to display real-time noise measurements on a map, just as you would visualize traffic conditions (green, yellow, red) on your maps app today—except that it’s displaying noise level. Another interesting development of crowdsourcing is the use of smartphone cameras to measure air pollution by asking users to orient their device toward the horizon at sunset and sunrise to use "haziness" as an indicator of relative pollution levels. While these crowdsourced apps are not intended to provide data that would stand up in a litigation scenario or other regulatory challenge, they make good general indicators and become "trending devices" when taken as a whole over time. From these examples, it’s not hard to imagine how a large company operating multiple locations of similar type and capacity could create and exploit their own "internal crowdsourcing" function in order to gain better insight into the consistency of their processes and trends, for both worker exposure levels and ambient pollution levels at multiple sites.



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