. An intelligent hot-desking model harnessing the power of occupancy sensing
. An intelligent hot-desking model harnessing the power of occupancy sensing
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发表时间：
2016
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通讯作者：
Nadine von Frankenberg
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作者：
Nadine von Frankenberg
在本文中，我们开发了一个模型，利用实验数据，从伦敦市中心的办公室，利用在商业热办公环境中的占用感测的力量。办公桌轮用是一种办公室资源管理方法，出现于90年代，通过放弃传统的地域性工作（即将特定的办公桌分配给特定的员工）来降低专业实践的真实的房地产成本。这在高真实的房地产成本地区（如纽约、伦敦）或高员工、低工资办公室，或因远程/客户现场工作而导致的办公桌空间利用不足被证明是一项重大开销的地方尤其可取。然而，不足之处往往在于所分配的工作环境是否适宜和适当。物联网可以在办公室中以一定的分辨率、速度和有效性生成新的数据集，这些数据集可以被考虑到办公桌分配中，根据适当的噪音水平、停留时间、设备要求、先前的存在以及与从事同一项目的其他人的接近程度等来分配座位。在本文中，我们表明，传感器数据可用于促进办公室资源管理，在我们的情况下，办公桌分配在一个热桌环境中利用基于活动的工作（或分配的“工作主题”），结果超过占用检测的成本。我们不仅能够根据高质量的占用数据优化办公桌的利用率，而且还展示了整体生产力的提高，因为个人尽可能多地分配他们喜欢的办公桌以及其他可以应用的优化。此外，我们还探讨了私营部门占用数据收集的增加如何对企业作为一个组织和整个城市产生关键优势。
In this paper we develop a model to harness the power of occupancy sensing in a commercial hot-desking environment utilising experimental data from an office in central London. Hot-desking is a method of office resource management that emerged in the 90s as a practice to reduce the real estate costs of professional practices, by abandoning traditional territorial working (i.e. where specific desks were allocated to specific employees). This was particularly desirable in high real estate cost areas such as New York, London or in high-staff, low-wage offices, or where underutilization of desk space due to remote/client site working was proved to be a significant overhead. However, the shortcoming is often in the suitability and appropriateness of allocated work environments. The Internet of Things could produce new data sets in the office at a resolution, speed and validity of which that they could be factored into desk-allocation, distributing seats based on appropriate noise levels, stay length, equipment requirements, previous presence, and proximity to others working on the same project, among many others. In this paper we show that sensor data can be used to facilitate office resources management, in our case desk allocation in a hot-desking environment utilising activity based working (or allocating by ‘work theme’), with results that outweigh the costs of occupancy detection. Not only are we able to optimise desk utilisation based on quality occupancy data, but also demonstrate how overall productivity increases, as individuals are allocated desks of their preference as much as possible among other enabling optimisations that can be applied. Moreover, we explore how an increase in occupancy data collection in the private sector could have key advantages for the business as an organization and the city as a whole.