Environmental Concerns

This week’s lecture was addressed by Dr. Lorrae Van Kerkhoff from the Fenner School of Environment and Society, with the underlying aim of highlighting notions of sustainability in engineering and computer system solutions.

The concept of sustainable development has been around for a while, we are all taught about it in schools, but do we really understand it? The textbook definition would define it as: development that meets the needs of the present, without compromising the ability of future generations to meet their own needs (Pooley et al., 2013). Nevertheless, despite of all the hullabaloo that surrounds everything that out to be green, why does all the data, from all the scientific investigations, exhibit a massive lack in the incorporation of such notions in the way that we do things?

While the concept of sustainable development has far reaching implications in seemingly everything industry, and human activity, we shall use an endogenous approach to investigate it within the ICT domain — for the sake of not getting embroiled in the complexity of the whole picture.

The Short-Sightedness of Current Development Models


The systems in place that we, today, use for development lack the incorporation of one very critical factors: the long-term implications of current activities. The capitalism-driven machine of the ICT domain — for the most part — is motivated with profit-generation and value addition to the industry (Reinhardt, Stavins, & Vietor, 2008); as a consequence, these developmental models become focused on short-term profit-generations with a complete disregard for what would happen 20 years from now, or 50 years from now, or 100 years from now. This does not paint a bright picture for the future of the industry.

In our lecture, the prospect of a safe and just space for humanity was discussed. This encompasses addressing climate change, land-use change, biodiversity loss, freshwater use, and human-influence amongst several other factors. It wa also discussed how the levels of commitment towards actually implementing sustainable development strategies have not met even the simplest of expected benchmarks. And it was proposed, that this inability to bring about substantial change is due to an indifference that has established itself at the core of the way in which we conduct our business.

A desperate need for a paradigm shift

Considering the nature of our conduct, and taking into consideration the fact that most of all of the scientific data from most of all of credible scientific sources states that the dangers of continuing on the current development paths shall inevitably result in the manifestation of grave consequences for the world as we know it, a paradigm shift of immense significance needs to be brought about in most, if not all, processes across the industrial domain.

Big changes do not occur overnight though; it can take years for change of any significance to occur. The right time to act is, therefore, not today, it was yesterday.

How can the Software Industry add value to a sustainable model?

Softwares, being at the core of almost all engineering systems across the entire industrial spectrum, have the potential to become the most significant enabling solution to drive digitization, dematerialization, optimization and integration of cross-platform and cross-institutional solutions for sustainable modes of conduct (United States, 2011).

The hazard mitigation or subsidizing potential of a systems engineering approach to create software systems may be manifested in the following sectors:

  • Energy

Smart Grids


A smart grid (Commission, 2008) is an electrical grid which incorporates several smart measures such as smart meters, smart appliances, renewable energy resources, and energy efficiency resources. At the moment, most of these platforms are hardware dependent, but as the cost of manufacturing of electrical and electrical grid components goes down, and computational power goes up, a more software intensive focus can be applied. This creates room for cross-platform optimization on a scale never before imagined.

Virtual Power Plants

Virtual Power Plants (VPPs) use concepts of distributed generation systems that use cross-platform, high-throughput computations across the constituents of its network to create and supply reliable power supply across the grid (Nezamabadi, Hossein, & Vahid, 2015). VPPs logically connect cogenerative micro combined heat and power (Landsbergen, 2009), photovoltaics (Loria, Dennis, Robert, & Edward, 2004), small-scale wind turbines and hydro-electricity plants etc. This virtual internetwork opens new avenues for power storage in large reserves, and changes the way in which optimization of power supply networks can be perceived

  • Transportation


Given a significant improvement in telecommuting technologies and platforms, a significant decrease in carbon pollution  could be observed due to elimination of the need to travel to the office (Gerard, David, & Lave, 2005). Additionally, it has the potential to have a considerable effect on driving down organizational operational costs, thereby increasing the profits (Sagner, 2011).



Through the use of advanced vehicular systems, a sustainable mobility culture could yield positive effects for climate protection, in addition to improving road safety. Eco-driving, at the moment, is largely dependent on users to make a set of smart decision, but as softwares becomes integral to operating system of vehicles, these decisions could be hard-wired into the vehicles, thus reaching new definitions of success (Barkenbus, 2010).

Logistic-Networks Optimization

Not only does this aid in achieving great value-return on investments, optimization of logistic networks can prove to have dramatic improvements in approaching service-level specifications, achieving mission-critical objectives, improving road-security, and most importantly driving down carbon emissions (Wang, Fan, Xiaofan, & Ning, 2011).

  • Agriculture and Land-Use

Livestock Management

Through the use of a barrage of RFID sensors, data analysis and information generation systems and improvements in wireless communications platforms, livestock management could become progressively automated (M. J. Darr et al., n.d.), and with time (as knowledge gets coupled with experience in decision support systems) significant improvements can be made on the environmental impact of livestock farming (May, Kenneth, & Bill, 1995; Sørensen, 1997).

A New Hope

We have barely touched the full potential of the use of a systems engineering approach towards creating green softwares systems and sustainable development policy initiatives. It can be reasonably observed that as the production and manufacturing costs of electrical and electronic components decreases, and as the availability of high-computational power becomes more conventionally available, we can tap into new definitions of sustainable engineering systems and policies.

However, it must be noted that change can only occur when it is at the centre of the movement that drive it. A softwares engineers, we are morally and ethically bound to take into consideration the fact that the products we create impact real lives, that each extra bit used while allocating memory space adds up and leads to more stress on the processor, that it leads to the processor suking in more power, that when it is scaled up for large scale and ultra-large scale systems, the cumulative impact of our work has a different level of impact on everything that it touches.



Barkenbus, J. N. (2010). Eco-driving: An overlooked climate change initiative. Energy Policy, 38(2), 762–769.

Commission, F. E. R. (2008, December). [Assessment of Demand Response and Advanced Metering]. Retrieved April 1, 2016, from http://www.ferc.gov/legal/staff-reports/12-08-demand-response.pdf

Gerard, D., David, G., & Lave, L. B. (2005). Implementing technology-forcing policies: The 1970 Clean Air Act Amendments and the introduction of advanced automotive emissions controls in the United States. Technological Forecasting and Social Change, 72(7), 761–778.

Landsbergen, P. (2009, June 30). Feasibility, beneficiality, and institutional compatibility of a micro-CHP virtual power plant in the Netherlands. TU Delft, Delft University of Technology. Retrieved from http://repository.tudelft.nl/assets/uuid:ee01fc77-2d91-43bb-83d3-847e787494af/Master_thesis_Landsbergen.pdf

Loria, D., Dennis, L., Robert, N., & Edward, S. (2004). The First Commercial Ocean Thermal Energy Conversion Power Plant: Taking a Renewable Energy Technology Project From Concept to Commercial Operation. In ASME 2004 Power Conference. http://doi.org/10.1115/power2004-52114

May, G. A., Kenneth, G., & Bill, H. (1995). Commercial use of space technologies for precision farming. In AIP Conference Proceedings. http://doi.org/10.1063/1.47247

  1. J. Darr, Darr, M. J., Zhao, L., Ehsani, M. R., Ward, J. K., & Stombaugh, A. T. S. (n.d.). EVALUATION OF CONTROLLER AREA NETWORK DATA COLLECTION SYSTEM IN CONFINED ANIMAL FEEDING OPERATIONS. In Livestock Environment VII, 18-20 May 2005, Beijing, China. http://doi.org/10.13031/2013.18363

Nezamabadi, H., Hossein, N., & Vahid, V. (2015). Two stage decision making of technical virtual power plants in electricity market via Nash-SFE equilibrium. In 2015 3rd International Istanbul Smart Grid Congress and Fair (ICSG). http://doi.org/10.1109/sgcf.2015.7354932

Pooley, R., Coady, J., Schneider, C., Linger, H., Barry, C., & Lang, M. (2013). Information Systems Development: Reflections, Challenges and New Directions. Springer Science & Business Media.

Reinhardt, F. L., Stavins, R. N., & Vietor, R. H. K. (2008). [Corporate Social Responsibility Through an Economic Lens]. Review of Environmental Economics and Policy, 2(2), 219–239.

Sagner, J. S. (2011). Cut costs using working capital management. Journal of Corporate Accounting & Finance, 22(3), 3–7.

Sørensen, J. T. (1997). Livestock Farming Systems: More Than Food Production : Proceedings of the Fourth International Symposium on Livestock Farming Systems.

United States. (2011). Energy Independence and Security Act of 2007. Books LLC.

Wang, F., Fan, W., Xiaofan, L., & Ning, S. (2011). A multi-objective optimization for green supply chain network design. Decision Support Systems, 51(2), 262–269.



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